內(nèi)容來(lái)自 DataSciComp，人工智能/數(shù)據(jù)科學(xué)比賽整理平臺(tái)志膀。
Github：iphysresearch/DataSciComp
本項(xiàng)目由 ApacheCN 強(qiáng)力支持肩袍。
2019世界機(jī)器人大賽—BCI腦控機(jī)器人大賽 暨 第三屆中國(guó)腦機(jī)接口比賽
http://www.worldrobotconference.com/html/jiqirendasai/saishi/2018/0314/290.html
5月9日-7月9日, 2019 // Host by DataFountain // Prize: ￥100,000
Note: 腦-機(jī)接口（BCI）是指通過(guò)對(duì)神經(jīng)系統(tǒng)電活動(dòng)和特征信號(hào)的收集形病、識(shí)別及轉(zhuǎn)化紧阔，使人腦發(fā)出的指令能夠直接傳遞給指定的機(jī)器終端，從而使人對(duì)機(jī)器人的控制和操作更為高效便捷烤黍，該項(xiàng)技術(shù)在人與機(jī)器人的交流溝通領(lǐng)域有著重大創(chuàng)新意義和使用價(jià)值知市，其已廣泛應(yīng)用于助殘康復(fù)、災(zāi)害救援速蕊、娛樂(lè)體驗(yàn)等多個(gè)領(lǐng)域嫂丙，并在改善殘疾人生活質(zhì)量中做出了巨大貢獻(xiàn)。
Entry Deadline:
Game of Deep Learning: Computer Vision Hackathon
https://datahack.analyticsvidhya.com/contest/game-of-deep-learning/
May 25 - Jun 10, 2019 // Host by Analytics Vidhya // Prize: Datahack Summit 2019 Tickets & Job Opportunities with AV
Note: Do you feel passionate about solving problems through deep learning?
Do you aspire to take data science to millions of people out there? Can the leader in you make people follow data science out of sheer passion?
If the answer to all the questions is yes – look no more. Analytics Vidhya is looking for evangelists who can carry and deliver their baton to the world.
Entry Deadline:
Urban Region Function Classification
https://dianshi.baidu.com/competition/30/rule
April 30th - September, 2019 // Host by 點(diǎn)石 // Prize: RMB150,000
Note: 2019 The 5th Baidu & XJTU Big Data Competition And The First IKCEST "One Belt One Road" International Big Data Competition.
Build models to classify the functions of urban areas with data of satellite images and user behavior from given geographical areas.
Entry Deadline:
Science of Science 數(shù)據(jù)黑客松
https://www.biendata.com/competition/hackathon/
06/18 - 06/12 2019 // Host by Biendata // Prize: 40,000元
Note: 科學(xué)論文雖然代表了人類(lèi)對(duì)自然最前沿的理解规哲，但大眾卻很難讀懂論文跟啤。所以論文發(fā)表后乙漓，科研機(jī)構(gòu)經(jīng)常會(huì)發(fā)布研究新聞稿解釋論文中的研究粟耻。本次比賽的任務(wù)是給定一篇科研新聞，找到這篇新聞描述的論文训裆。
提交數(shù)據(jù)格式: 新聞數(shù)據(jù)測(cè)試集press_test.csv中的每篇新聞都是在報(bào)道論文測(cè)試集paper_test.csv中的一篇論文袄简。對(duì)于每篇新聞武福，選手需要從paper_test.csv中選出三篇最相關(guān)的論文。參賽者需要在訓(xùn)練集上訓(xùn)練模型痘番，并對(duì)新聞和論文的相關(guān)行進(jìn)行預(yù)測(cè)，最終可以標(biāo)注 Top 3 的匹配結(jié)果平痰。注意：預(yù)測(cè)出的匹配論文之間存在順序汞舱，按照預(yù)測(cè)得分，從大到小排序宗雇。
本次黑客松任務(wù)即掛靠這次會(huì)議昂芜。在4天的時(shí)間里，參賽選手需要通過(guò)平臺(tái)提交預(yù)測(cè)結(jié)果赔蒲。前三名選手將獲得4萬(wàn)元獎(jiǎng)金泌神，并被邀請(qǐng)到會(huì)議上介紹獲獎(jiǎng)方法良漱。
Entry Deadline:
Objects 365 圖片物體檢測(cè)
https://www.biendata.com/competition/objects365/
04/29 - 06/10 2019 // Host by Biendata & CVPR 2019 // Prize: $20,000
Note: Objects365是一個(gè)全新的數(shù)據(jù)集，旨在促進(jìn)對(duì)自然場(chǎng)景不同對(duì)象的檢測(cè)研究欢际。Objects365在638K張圖像上標(biāo)注了365個(gè)對(duì)象類(lèi)母市，訓(xùn)練集中共有超過(guò)1000萬(wàn)個(gè)邊界框。因此损趋，這些標(biāo)注涵蓋了發(fā)生在各種場(chǎng)景類(lèi)別中的常見(jiàn)對(duì)象患久。
Entry Deadline:
Crowd Human 人體檢測(cè)
https://www.biendata.com/competition/crowdhuman/
04/29 - 06/10 2019 // Host by Biendata & CVPR 2019 // Prize: $10,000
Note: CrowdHuman是目前最大的人體檢測(cè)數(shù)據(jù)集，帶有充分的標(biāo)注信息浑槽，圖片來(lái)源具有豐富的多樣性蒋失。包含15000張訓(xùn)練集，4370張驗(yàn)證集和5000張測(cè)試集桐玻，在數(shù)據(jù)集中篙挽，總共有340K個(gè)人體目標(biāo)，平均每張圖片有22.6個(gè)人镊靴，數(shù)據(jù)集中有各種各樣的遮擋場(chǎng)景铣卡。每個(gè)人的實(shí)例都有一個(gè)頭部邊界框、可見(jiàn)區(qū)域邊界框和全身邊界框邑闲。
Entry Deadline:
2019中國(guó)高校計(jì)算機(jī)大賽——大數(shù)據(jù)挑戰(zhàn)賽
https://www.kesci.com/home/competition/5cb80fd312c371002b12355f
2019-04-28 至 2019-06-25 // Host by Kesci // Prize: 30萬(wàn)元人民幣
Note: 2019大數(shù)據(jù)挑戰(zhàn)賽（以下簡(jiǎn)稱(chēng)“大賽”）是在中國(guó)高校計(jì)算機(jī)大賽主辦單位的指導(dǎo)下算行，由清華大學(xué)、南開(kāi)大學(xué)與字節(jié)跳動(dòng)公司聯(lián)合主辦苫耸，亞馬遜AWS提供資源支持以及科賽提供競(jìng)賽平臺(tái)支持州邢，并以企業(yè)真實(shí)場(chǎng)景和實(shí)際數(shù)據(jù)為基礎(chǔ)的高端算法競(jìng)賽。大賽面向全球高校在校生開(kāi)放褪子，旨在提升高校學(xué)生對(duì)數(shù)據(jù)分析與處理的算法研究與技術(shù)應(yīng)用能力量淌，探索大數(shù)據(jù)的核心科學(xué)與技術(shù)問(wèn)題，嘗試創(chuàng)新大數(shù)據(jù)技術(shù)嫌褪，推動(dòng)大數(shù)據(jù)的產(chǎn)學(xué)研用呀枢，本次大賽鼓勵(lì)高校教師參與指導(dǎo)。
預(yù)選賽——文本情感分類(lèi)模型
正式賽題——文本點(diǎn)擊率預(yù)估（5月26日開(kāi)賽）
Entry Deadline:
2019 EE331 - Colorization
https://competitions.codalab.org/competitions/23046
May 27 - June 15, 2019 // Host by CodaLab // Prize: NaN
Note: Our goal is to make colorization from input images.
The normal images are composed of RGB values, but we can represent these images into LAB values.
In here, L means lightness.
We cannot know the color of the image without the A and B values.
Entry Deadline:
阿里巴巴優(yōu)酷視頻增強(qiáng)和超分辨率挑戰(zhàn)賽
April 11 - September, 2019 // Host by 天池 & YOUKU // Prize: ￥230000
Note: 比賽要求通過(guò)訓(xùn)練樣本對(duì)視頻增強(qiáng)和超分模型進(jìn)行建模笼痛，對(duì)測(cè)試集中的低分辨率視頻樣本預(yù)測(cè)高分辨率視頻裙秋。其中，高分辨率視頻來(lái)自?xún)?yōu)酷高清媒資庫(kù)缨伊，優(yōu)酷擁有視頻的知識(shí)產(chǎn)權(quán)摘刑。低分辨率視頻的生成模型是模擬實(shí)際業(yè)務(wù)中的噪聲模式。
Entry Deadline:
2019 AIWIN 5G環(huán)境下無(wú)人駕駛挑戰(zhàn)賽 / Self-driving Car Challenge under 5G Environment
https://www.kesci.com/home/competition/5cbd8083c7d626002beb280d
2019-04-25 至 2019-07-31 // Host by Kesci // Prize: ￥ 200,000 + SAIL獎(jiǎng)推薦
Note: Under 5G network environment, Self-driving car faces new opportunities and challenges. International teams are invited to join us at LinGang’s Self-driving car closed test zone to conduct real road test and virtual scene test.
1刻坊、無(wú)人駕駛 5G應(yīng)用挑戰(zhàn) / Self-driving Car 5G application challenge
2枷恕、自動(dòng)駕駛算法虛擬場(chǎng)景挑戰(zhàn) / Automatic driving algorithm Virtual scene Challenge
Entry Deadline:
Jigsaw Unintended Bias in Toxicity Classification
https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification
Now - July 10, 2019 // Host by Kaggle // Prize: $65,000
Note: This is a Kernels-only competition.
Detect toxicity across a diverse range of conversations
Entry Deadline:
Learning to Run a Power Network (L2RPN 2019)
May 15th - Jul 14th, 2019 // Host by CodaLab & IJCNN 2019 // Prize: 3000$ travel expenses
Note: The challenge is based on an environment (and not solely a dataset) in which an agent can learn by interactions.
Entry Deadline:
The 1st Chinese Audio-Textual Spoken Language Understanding Challenge (CATSLU)
https://sites.google.com/view/CATSLU/home
15/03 - 12/08, 2019 // Host by ICMI 2019 // Prize: NaN
Note: The spoken language understanding (SLU) is a key component of spoken dialogue system (SDS), parsing user's utterances into corresponding semantic concepts. To fully investigate these problems and promote application of spoken dialogue system, we will release a multi-turn task-oriented Chinese spoken dialog dataset and organize the first open, audio-text based Chinese Task Oriented Spoken Language Understanding Challenge. This challenge consists of two sub-challenges:
SLU in domain
Domain adaptation of SLU
Entry Deadline:
Instant Gratification
https://www.kaggle.com/c/instant-gratification
Now - June 20, 2019 // Host by Kaggle // Prize: $5,000
Note: A synchronous Kernels-only competition
Entry Deadline:
Data Science for Good: City of Los Angeles
https://www.kaggle.com/c/data-science-for-good-city-of-los-angeles
May 8th - June 21, 2019 // Host by Kaggle // Prize: $15,000
Note: Help the City of Los Angeles to structure and analyze its job descriptions.
The goal is to convert a folder full of plain-text job postings into a single structured CSV file and then to use this data to: (1) identify language that can negatively bias the pool of applicants; (2) improve the diversity and quality of the applicant pool; and/or (3) make it easier to determine which promotions are available to employees in each job class.
Entry Deadline:
Virtual Creatures Competition
https://virtualcreatures.github.io
Now - June 23, 2019 // Host by GECCO 2019 // Prize: NaN
Note: The purpose of the contest is not to build a system to solve a task better than any other system; rather, the goal is to engage our imagination and creativity---to expand our conception of life and intelligence, and how these things might materialize.
Entry Deadline:
The 1st Mandarin Audio-Visual Speech Recognition Challenge (MAVSR)
http://vipl.ict.ac.cn/homepage/mavsr/index.html
April 11 - August 8, 2019 // Host by ICMI 2019 // Prize: ~30,000 RMB
Note: This challenge aims at exploring the complementarity between visual and acoustic information in real-world speech recognition systems, and will be held at ACM International Conference on Multimodal Interaction (ICMI) 2019.
Sub-challenge 1: Closed-set word-level speech recognition
Sub-challenge 2: Open-set word-level speech recognition
Sub-challenge 3: Visual keyword spotting
Entry Deadline:
PharmaCoNER: Pharmacological Substances, Compounds and proteins and Named Entity Recognition track
http://temu.bsc.es/pharmaconer/
March 18 - November 3, 2019 // Host by CodaLab // Prize: 1,700€x2
Note: For this task we have prepared a manually classified collection of clinical case sections derived from Open access Spanish medical publications, named the Spanish Clinical Case Corpus (SPACCC). The corpus contains a total of 1000 clinical cases / 396,988 words. It is noteworthy to say that this kind of narrative shows properties of both, the biomedical and medical literature as well as clinical records.
Track 1: NER offset and entity classification.
Track 2: Concept indexing.
Entry Deadline:
政府治理大數(shù)據(jù)應(yīng)用算法大賽
http://campus.chinahr.com/pages/cetctwo/
2019-05-27 至 2019-08-31 // Host by 中電科大數(shù)據(jù)研究院有限公司 // Prize: ￥14萬(wàn)
Note: 國(guó)內(nèi)外全日制在校大學(xué)生（包括全日制本科、碩士谭胚、博士研究生等非2019屆畢業(yè)生）徐块，熱愛(ài)算法建模未玻、熱愛(ài)數(shù)據(jù)分析、熱愛(ài)應(yīng)用開(kāi)發(fā)等均可參賽胡控。
本輪賽事僅設(shè)1題: 政策公文中的語(yǔ)義搜索(需要根據(jù)輸入的問(wèn)題扳剿，返回對(duì)應(yīng)的政策內(nèi)容，以及相應(yīng)的公文名稱(chēng)和具體條例)
Entry Deadline:
轉(zhuǎn)子部件脫落故障預(yù)測(cè) (Prognosis of Rotor Parts Fly-off)
5月24日 - 7月22日, 2019 // Host by 中國(guó)信息通信研究院 // Prize: ￥200,000
Note: 第三屆工業(yè)大數(shù)據(jù)創(chuàng)新競(jìng)賽
Background: For large rotating machines, due to the high rotating speed and tremendous momentum of the rotor, the centrifugal force may lead to the loose or flying apart of the rotor parts, which brings a great threat to the operation safety of the equipment. This type of fault could lead to high maintenance cost and significant economic loss. The capture of the early symptom of rotor faults is relatively difficult and has become a worldwide challenge in the field of prognostics. It will bring significant safety value and economic benefits if the big data-based methods can detect and predict incipient faults.
賽事簡(jiǎn)要：大型旋轉(zhuǎn)機(jī)組設(shè)備高速旋轉(zhuǎn)铜犬、動(dòng)能巨大舞终，轉(zhuǎn)子部件脫落故障給設(shè)備安全運(yùn)行帶來(lái)巨大威脅。而且這類(lèi)故障維修成本高癣猾、耗時(shí)長(zhǎng)敛劝，早期征兆難以捕捉，是故障預(yù)測(cè)的世界性難題纷宇。如果能通過(guò)大數(shù)據(jù)方法夸盟，實(shí)現(xiàn)此故障征兆的早期發(fā)現(xiàn)和程度預(yù)測(cè)，將帶來(lái)顯著的安全價(jià)值和經(jīng)濟(jì)效益像捶。
Entry Deadline:
RecSys Challenge 2019
http://www.recsyschallenge.com/2019/
March - September, 2019 // Host by ACM RecSys conference // Prize: NaN
Note: This year's challenge is to develop a session-based and context-aware recommender system to adapt a list of accommodations according to the needs of the user.
Entry Deadline:
2019中國(guó)‘法研杯’司法人工智能挑戰(zhàn)賽（CAIL2019）
5月15日 - 7月26日, 2019 // Host by 中國(guó)中文信息學(xué)會(huì) (CIPS) // Prize: 60,000RMB
Note: 本次挑戰(zhàn)賽聚焦在法律要素抽取上陕、法律閱讀理解、相似案例匹配三個(gè)真實(shí)場(chǎng)景的任務(wù)拓春，提供海量的已標(biāo)注的法律文書(shū)數(shù)據(jù)释簿，旨在為研究者提供學(xué)術(shù)交流平臺(tái)，推動(dòng)語(yǔ)言理解和人工智能領(lǐng)域技術(shù)在法律領(lǐng)域的應(yīng)用硼莽，促進(jìn)法律人工智能事業(yè)的發(fā)展庶溶。今年預(yù)計(jì)于10月在北京舉辦頒獎(jiǎng)會(huì)和技術(shù)研討會(huì)。誠(chéng)邀學(xué)術(shù)界和工業(yè)界的研究者和開(kāi)發(fā)者積極參與懂鸵，比賽中發(fā)現(xiàn)的重大基礎(chǔ)性問(wèn)題偏螺，在國(guó)家自然科學(xué)基金專(zhuān)項(xiàng)資金中將予以重點(diǎn)考慮！
Entry Deadline:
CMRC 2019: The Third Evaluation Workshop on Chinese Machine Reading Comprehension
https://hfl-rc.github.io/cmrc2019/
May 23th - Oct 18th, 2019 // Host by CodaLab & 中國(guó)中文信息學(xué)會(huì)計(jì)算語(yǔ)言學(xué)專(zhuān)業(yè)委員會(huì)（CIPS-CL） & 哈工大訊飛聯(lián)合實(shí)驗(yàn)室（HFL） & 科大訊飛股份有限公司 // Prize: 35,000 CNY
Note: 第三屆“訊飛杯”中文機(jī)器閱讀理解（CMRC 2019）的任務(wù)是句子級(jí)填空型閱讀理解（Sentence Cloze-Style Machine Reading Comprehension, SC-MRC）匆光。 根據(jù)給定的一個(gè)敘事篇章以及若干個(gè)從篇章中抽取出的句子套像，參賽者需要建立模型將候選句子精準(zhǔn)的填回原篇章中，使之成為完整的一篇文章终息。本任務(wù)需要機(jī)器能夠根據(jù)上下文的邏輯關(guān)系判斷空缺部分的內(nèi)容夺巩，進(jìn)一步提升了機(jī)器閱讀理解的難度。
Entry Deadline:
Bi-Objective Optimisation for the Travelling Thief Problem
https://www.egr.msu.edu/coinlab/blankjul/gecco19-thief/
Now - June 30, 2019 // Host by GECCO 2019 // Prize: NaN
Note: The goal of this competition is to provide a platform for researchers in computational intelligence working on multi-component optimization problems.
Entry Deadline:
Black Box Optimization Competition (BBComp)
February 4 - June 30, 2019 // Host by GECCO 2019 // Prize: NaN
Note: The Black Box Optimization Competition is the first competition platform in the continuous domain where test problems are truly black boxes to participants. The only information known to optimizer and participant is the dimension of the problem, bounds on all variables, and a budget of black box queries. The competition covers single- and multi-objective optimization.
Entry Deadline:
Internet of Things: Online Event Detection for Drinking Water Quality Control
http://www.spotseven.de/gecco/gecco-challenge/
End of January/Start of February - June 30, 2019 // Host by GECCO 2019 // Prize: NaN
Note: The task of this years competition is to develop an anomaly detection algorithm for the water- and environmental data set. Early identification of anomalies in water quality data is a challenging task.
Entry Deadline:
CCKS 2019 人物關(guān)系抽取
https://www.biendata.com/competition/ccks_2019_ipre/
04/20 - 07/25 2019 // Host by Biendata // Prize: ￥43,000
Note: 在本次任務(wù)中周崭，我們重點(diǎn)關(guān)注人物之間的關(guān)系抽取研究柳譬，簡(jiǎn)稱(chēng)IPRE（Inter-Personal Relationship Extraction）。給定一組人物實(shí)體對(duì)和包含該實(shí)體對(duì)的句子休傍，找出給定實(shí)體對(duì)在已知關(guān)系表中的關(guān)系。
Entry Deadline:
Pose Estimation Challenge
https://kelvins.esa.int/satellite-pose-estimation-challenge/
Feb. 1, 2019 - July 1, 2019 // Host by Kelvins // Prize: NaN
Note: One camera, one image, one pose.
In this challenge, you are tasked to estimate the pose of the Tango spacecraft from its synthetic and real images captured using computer graphics and a robotic testbed, respectively.
Entry Deadline:
Microsoft AI Challenge India 2018
https://competitions.codalab.org/competitions/20616
Nov. 19, 2018 - July 1, 2019 // Host by CodaLab // Prize: NaN
Note: The Microsoft AI Challenge India 2018 is over now. The page is active for learning purposes only. Problem statement:
"Given a user query and candidate passages corresponding to each, the task is to mark the most relevant passage which contains the answer to the user query."
Entry Deadline:
SMP 2019 ETST 第二屆文本溯源技術(shù)評(píng)測(cè)
https://www.biendata.com/competition/smpetst2019/
05/20 - 07/08 2019 // Host by Biendata // Prize: $19,000
Note: SMP 2019文本溯源評(píng)測(cè)由中國(guó)中文信息學(xué)會(huì)社會(huì)媒體處理專(zhuān)業(yè)委員會(huì)主辦蹲姐，黑龍江工程學(xué)院承辦磨取。本次技術(shù)評(píng)測(cè)以科研立項(xiàng)或成果創(chuàng)新型審查為應(yīng)用背景人柿，文本溯源的目標(biāo)是判斷一個(gè)文本的內(nèi)容是否復(fù)制或改編于另外一個(gè)或者多個(gè)文本。文本溯源技術(shù)在學(xué)術(shù)誠(chéng)信檢測(cè)忙厌、搜索引擎優(yōu)化等領(lǐng)域有廣泛應(yīng)用凫岖。
Entry Deadline:
Data Science for Good: CareerVillage.org
https://www.kaggle.com/c/data-science-for-good-careervillage
Feb 26th - April 30th, 2019 // Host by Kaggle // Prize: $15,000
Note: Match career advice questions with professionals in the field
Entry Deadline:
CCKS 2019 中文短文本的實(shí)體鏈指
https://www.biendata.com/competition/ccks_2019_el/
04/20 - 07/30 2019 // Host by Biendata // Prize: ￥10,000
Note: 輸入文件包括若干行中文短文本。輸出文本每一行包括此中文短文本的實(shí)體識(shí)別與鏈指結(jié)果逢净，需識(shí)別出文本中所有mention（包括實(shí)體與概念）哥放，每個(gè)mention包含信息如下：mention在給定知識(shí)庫(kù)中的ID，mention名和在中文短文本中的位置偏移爹土。
Entry Deadline:
KDD Cup 2019
https://www.4paradigm.com/competition/kddcup2019
Apr 1st - Jul 16th, 2019 // Host by 4Paradigm & ChaLearn & CodaLab // Prize: $65,000
Note: The 5th AutoML Challenge: AutoML for Temporal Relational Data
In this challenge, participants are invited to develop AutoML solutions to binary classification problems for temporal relational data.
Entry Deadline:
7th Emotion Recognition in the Wild Challenge (EmotiW)
https://sites.google.com/view/emotiw2019
February - July, 2019 // Host by ICMI 2019 // Prize: NaN
Note: The goal of this challenge is to extend and carry forward the new common platform for evaluation of emotion recognition methods in real-world conditions defined in EmotiW2018 Grand Challenge held at the ACM International Conference on Multimodal Interaction 2018. This year there will be three sub-challenges:
Audio-video based emotion recognition sub-challenge (AV)
Group-level Cohesion sub-challenge (GC)
Engagement prediction in the Wild (EW)
Entry Deadline:
Shared Task on Hierarchical Classification of Blurbs
https://competitions.codalab.org/competitions/21226
Feb. 1 - Aug, 2019 // Host by CodaLab & KONVENS 2019 // Prize: NaN
Note: This task is focusing on classifying German books into their respective hierarchically structured writing genres using short advertisement texts (Blurbs) and further meta information such as author, page number, release date, etc.
Entry Deadline:
eBay SIGIR 2019 eCommerce Search Challenge: High Accuracy Recall Task
https://sigir-ecom.github.io/data-task.html
May 17 - July 25, 2019 // Host by EvalAI & The 2019 SIGIR Workshop On eCommerce // Prize: NaN
Note: The challenge data consists of a set of popular search queries and a fair size set of candidate documents. Challenge participants make a boolean relevant-or-not decision for each query-document pair. Human judgments are used to create labeled training and evaluation data for a subset of the query-document pairs. Evaluation of submissions will be based on the traditional F1 metric, incorporating components of both recall and precision.
Entry Deadline:
2019 年縣域農(nóng)業(yè)大腦AI挑戰(zhàn)賽
https://tianchi.aliyun.com/competition/entrance/231717/introduction
6月05 - 9月25, 2019 // Host by 天池 // Prize: ￥300000
Note: 本次大賽甥雕，我們選擇了具有獨(dú)特的地理環(huán)境、氣候條件以及人文特色的貴州省興仁市作為研究區(qū)域胀茵，聚焦當(dāng)?shù)氐奶厣珒?yōu)勢(shì)產(chǎn)業(yè)和支柱產(chǎn)業(yè)——薏仁米產(chǎn)業(yè)社露， 以薏仁米作物識(shí)別以及產(chǎn)量預(yù)測(cè)為比賽命題，要求選手開(kāi)發(fā)算法模型琼娘，通過(guò)無(wú)人機(jī)航拍的地面影像峭弟，探索作物分類(lèi)的精準(zhǔn)算法，識(shí)別薏仁米脱拼、玉米瞒瘸、烤煙三大作物類(lèi)型，提升作物識(shí)別的準(zhǔn)確度熄浓，降低對(duì)人工實(shí)地勘察的依賴(lài)情臭，提升農(nóng)業(yè)資產(chǎn)盤(pán)點(diǎn)效率，并結(jié)合產(chǎn)量標(biāo)注數(shù)據(jù)預(yù)測(cè)當(dāng)年的薏仁米產(chǎn)量玉组，提升農(nóng)業(yè)精準(zhǔn)管理能力谎柄。
Entry Deadline:
CCKS 2019 中文知識(shí)圖譜問(wèn)答
https://www.biendata.com/competition/ccks_2019_6/
04/20 - 07/30 2019 // Host by Biendata // Prize: ￥15,000
Note: 本評(píng)測(cè)任務(wù)為基于中文知識(shí)圖譜的自然語(yǔ)言問(wèn)答，簡(jiǎn)稱(chēng)CKBQA （Chinese Knowledge Base Question Answering）惯雳。即輸入一句中文問(wèn)題朝巫，問(wèn)答系統(tǒng)從給定知識(shí)庫(kù)中選擇若干實(shí)體或?qū)傩灾底鳛樵搯?wèn)題的答案。問(wèn)題均為客觀事實(shí)型石景，不包含主觀因素劈猿。理解并回答問(wèn)題的過(guò)程中可能需要進(jìn)行實(shí)體識(shí)別、關(guān)系抽取潮孽、語(yǔ)義解析等子任務(wù)揪荣。這些子任務(wù)的訓(xùn)練可以使用額外的資源，但是最終的答案必須來(lái)自給定的知識(shí)庫(kù)往史。
Entry Deadline:
Online Challenge: Build A Recommendation Engine (Powered by IBM Cloud)
https://datahack.analyticsvidhya.com/contest/build-a-recommendation-engine-powered-by-ibm-cloud/
24 Jan - 25 July, 2019 // Host by Analytics Vidhya // Prize: INR 50,000
Note: You are expected to build a high performing recommendation engine using any framework of your choice. You are encouraged to use IBM Watson Studio Apache spark based Jupyter notebook.
Entry Deadline:
WIDER Face & Person Challenge 2019
http://wider-challenge.org/2019.html
May 8 - July 25, 2019 // Host by CodaLab & ICCV 2019 & 商湯 & Amazon // Prize: cash prize and AWS credits
Note: Following the success of the First WIDER Challenge Workshop, we organize a new round of challenge in conjunction with ICCV 2019. The challenge centers around the problem of precise localization of human faces and bodies, and accurate association of identities. It comprises of four tracks:
WIDER Face Detection
http://wider-challenge.org/comingsoon.html, aims at soliciting new approaches to advance the state-of- the-art in face detection.
WIDER Pedestrian Detection
https://competitions.codalab.org/competitions/22852, has the goal of gathering effective and efficient approaches to address the problem of pedestrian detection in unconstrained environments.
WIDER Cast Search by Portrait
https://competitions.codalab.org/competitions/22833, presents an exciting challenge of searching cast across hundreds of movies.
WIDER Person Search by Language
https://competitions.codalab.org/competitions/22864, aims to seek new approaches to search person by natural language.
Entry Deadline:
第四屆魔鏡杯大賽
https://ai.ppdai.com/mirror/goToMirrorDetail?mirrorId=17
2019-05-28 至 2019-07-27 // Host by 拍拍貸·AI & DC // Prize: ￥370000
Note: 本次比賽以互聯(lián)網(wǎng)金融信貸業(yè)務(wù)為背景仗颈，參賽選手需要利用提供的數(shù)據(jù)，預(yù)測(cè)資產(chǎn)組合在未來(lái)一段時(shí)間內(nèi)每日的回款金額。賽題涵蓋了信貸違約預(yù)測(cè)挨决、現(xiàn)金流預(yù)測(cè)等金融領(lǐng)域常見(jiàn)問(wèn)題请祖，同時(shí)又是復(fù)雜的時(shí)序問(wèn)題和多目標(biāo)預(yù)測(cè)問(wèn)題。
Entry Deadline:
CCKS 2019 面向金融領(lǐng)域的事件主體抽取
https://www.biendata.com/competition/ccks_2019_4/
05/01 - 07/30 2019 // Host by Biendata // Prize: ￥15,000
Note: 本次評(píng)測(cè)任務(wù)的主要目標(biāo)是從真實(shí)的新聞?wù)Z料中脖祈，抽取特定事件類(lèi)型的主體肆捕。即給定一段文本T，和文本所屬的事件類(lèi)型S盖高，從文本T中抽取指定事件類(lèi)型S的事件主體慎陵。
Entry Deadline:
DeepFashion2 Challenge 2019
https://sites.google.com/view/cvcreative/deepfashion2?authuser=0
May 27 - July 30, 2019 // Host by CodaLab // Prize: NaN
Note: DeepFashion2 (github) is a comprehensive fashion dataset. It contains 491K diverse images of 13 popular clothing categories from both commercial shopping stores and consumers. It totally has 801K clothing clothing items, where each item in an image is labeled with scale, occlusion, zoom-in, viewpoint, category, style, bounding box, dense landmarks and per-pixel mask.There are also 873K Commercial-Consumer clothes pairs.
The dataset is split into a training set (391K images), a validation set (34k images), and a test set (67k images).
Track 1 Clothes Landmark Estimation
https://competitions.codalab.org/competitions/23095
Track 2 Clothes Retrieval
https://competitions.codalab.org/competitions/23098
Entry Deadline:
第三屆"長(zhǎng)風(fēng)杯"大數(shù)據(jù)分析與挖掘競(jìng)賽
http://contest.cfdsj.cn/index/care
2019-05-15 至 2019-10-31 // Host by 長(zhǎng)風(fēng)大數(shù)據(jù)平臺(tái) // Prize: ￥5萬(wàn)
Note: 第三屆“長(zhǎng)風(fēng)杯”大數(shù)據(jù)分析與挖掘競(jìng)賽是一場(chǎng)面向全國(guó)普通高等院校經(jīng)濟(jì)與管理類(lèi)、信息技術(shù)類(lèi)等專(zhuān)業(yè)在校大學(xué)生的全國(guó)性賽事喻奥。
長(zhǎng)風(fēng)大數(shù)據(jù)平臺(tái)將向本次競(jìng)賽的參賽者免費(fèi)開(kāi)放物流席纽、電商、交通映凳、公共胆筒、貿(mào)易等多行業(yè)的海量數(shù)據(jù)資源；其他生產(chǎn)型/服務(wù)型企業(yè)所提供真實(shí)數(shù)據(jù)诈豌。
Entry Deadline:
Northeastern SMILE Lab - Recognizing Faces in the Wild
https://www.kaggle.com/c/recognizing-faces-in-the-wild/overview/description
Now - August 8, 2019 // Host by Kaggle // Prize: NaN
Note: Can you determine if two individuals are related?
Entry Deadline:
首屆中文NL2SQL挑戰(zhàn)賽
https://tianchi.aliyun.com/competition/entrance/231716/introduction
6月24 - 9月, 2019 // Host by 天池 // Prize: ￥十五萬(wàn)
Note: 首屆中文NL2SQL挑戰(zhàn)賽仆救，使用金融以及通用領(lǐng)域的表格數(shù)據(jù)作為數(shù)據(jù)源，提供在此基礎(chǔ)上標(biāo)注的自然語(yǔ)言與SQL語(yǔ)句的匹配對(duì)矫渔，希望選手可以利用數(shù)據(jù)訓(xùn)練出可以準(zhǔn)確轉(zhuǎn)換自然語(yǔ)言到SQL的模型彤蔽。
Entry Deadline:
Segmentation of THoracic Organs at Risk in CT images (SegTHOR)
https://competitions.codalab.org/competitions/21012
Jan. 5 - Aug 8, 2019 // Host by CodaLab & ISBI 2019 // Prize: NaN
Note: The goal of the SegTHOR challenge is to automatically segment 4 OAR: heart, aorta, trachea, esophagus. Participants will be provided with a training set 40 CT scans with manual segmentation. The test set will include 20 CT scans.
Entry Deadline:
Challenges and Opportunities in Automated Coding of COntentious Political Events (Cope 2019) @Euro CSS 2019
6/7 - 9/2, 2019 // Host by CodaLab & Euro CSS 2019 // Prize: NaN
Note: We use English online news archives from India and China as data sources to create the training and test corpora. India and China are the source and the target countries respectively in our setting.
Entry Deadline:
ARIEL Data Challenge Series 2019
https://ariel-datachallenge.azurewebsites.net
~ 15th of August 2019 // Host by ECML-PKDD 2019 // Prize: Eternal gratitude ... or a bottle of wine.
Note: ARIEL, a mission to make the first large-scale survey of exoplanet atmospheres, has launched a global competition series to find innovative solutions for the interpretation and analysis of exoplanet data. You can find our press release here.
The first ARIEL Data Challenge
https://ariel-datachallenge.azurewebsites.net/ML invites professional and amateur data scientists around the world to use Machine Learning (ML) to remove noise from exoplanet observations caused by starspots and by instrumentation.
A second ARIEL Data Challenge
https://ariel-datachallenge.azurewebsites.net/retrieval that focuses on the retrieval of spectra from simulations of cloudy and cloud-free super-Earth and hot-Jupiter data was also launched today.
A further data analysis challenge
https://ariel-datachallenge.azurewebsites.net/# to create pipelines for faster, more effective processing of the raw data gathered by the mission will be launched in June.
Entry Deadline:
iFLYTEK AI 開(kāi)發(fā)者大賽
http://challenge.xfyun.cn/2019/
5月21日 - 10月14日, 2019 // Host by 訊飛開(kāi)放平臺(tái) // Prize: 100萬(wàn) RMB
Note: "iFLYTEK AI 開(kāi)發(fā)者大賽"是由科大訊飛發(fā)起的頂尖人工智能競(jìng)賽平臺(tái)，匯聚產(chǎn)學(xué)研各界力量庙洼，面向全球開(kāi)發(fā)者發(fā)起數(shù)據(jù)算法及創(chuàng)新應(yīng)用類(lèi)挑戰(zhàn)顿痪，推動(dòng)人工智能前沿科學(xué)研究和創(chuàng)新成果轉(zhuǎn)化，培育人工智能產(chǎn)業(yè)人才油够，助力人工智能生態(tài)建設(shè)蚁袭。 2019 年，第二屆 iFLYTEK AI 開(kāi)發(fā)者大賽將繼續(xù)開(kāi)放科大訊飛優(yōu)質(zhì)大數(shù)據(jù)資源及人工智能核心技術(shù)石咬，面向全球開(kāi)發(fā)者發(fā)起數(shù)據(jù)算法及創(chuàng)新應(yīng)用類(lèi)挑戰(zhàn)揩悄。
阿爾茨海默綜合癥預(yù)測(cè)挑戰(zhàn)賽: 基于老年人在特定圖片描述任務(wù)中產(chǎn)生的語(yǔ)音，給定語(yǔ)音數(shù)據(jù)中提取出的聲學(xué)特征鬼悠、主被試對(duì)話(huà)的切分信息删性、人工文本轉(zhuǎn)寫(xiě)結(jié)果以及對(duì)應(yīng)的認(rèn)知標(biāo)簽，建立2分類(lèi)模型預(yù)測(cè)認(rèn)知標(biāo)簽（正郴牢眩或認(rèn)知障礙）蹬挺。
移動(dòng)廣告反欺詐算法挑戰(zhàn)賽: 移動(dòng)廣告反欺詐需要強(qiáng)大的數(shù)據(jù)作為支撐，本次大賽提供了訊飛AI營(yíng)銷(xiāo)云海量的現(xiàn)網(wǎng)流量數(shù)據(jù)作為訓(xùn)練樣本它掂，參賽選手需基于提供的樣本構(gòu)建模型巴帮，預(yù)測(cè)流量作弊與否。
大數(shù)據(jù)應(yīng)用分類(lèi)標(biāo)注挑戰(zhàn)賽: 選手基于提供的應(yīng)用二級(jí)分類(lèi)標(biāo)簽以及若干隨機(jī)應(yīng)用標(biāo)注樣本，實(shí)現(xiàn)應(yīng)用分類(lèi)標(biāo)注算法（每個(gè)應(yīng)用一個(gè)標(biāo)簽榕茧，以應(yīng)用最主要屬性對(duì)應(yīng)的標(biāo)簽為該應(yīng)用的標(biāo)簽）发乔。
工程機(jī)械核心部件壽命預(yù)測(cè)挑戰(zhàn)賽: 由中科云谷科技有限公司提供某類(lèi)工程機(jī)械設(shè)備的核心耗損性部件的工作數(shù)據(jù)，包括部件工作時(shí)長(zhǎng)雪猪、轉(zhuǎn)速、溫度起愈、電壓只恨、電流等多類(lèi)工況數(shù)據(jù)。希望參賽者利用大數(shù)據(jù)分析抬虽、機(jī)器學(xué)習(xí)官觅、深度學(xué)習(xí)等方法，提取合適的特征阐污、建立合適的壽命預(yù)測(cè)模型休涤，預(yù)測(cè)核心耗損性部件的剩余壽命。
Entry Deadline:
Predicting Molecular Properties
https://www.kaggle.com/c/champs-scalar-coupling
Now - August 28, 2019 // Host by Kaggle // Prize: $30,000
Note: Can you measure the magnetic interactions between a pair of atoms?
Entry Deadline:
Challenge on Deep Learning based Loop Filter for Video Coding
http://challenge.ai.iqiyi.com/detail?raceId=5b112a742a360316a898ff50
May, 25th - May, 31st, 2018 // Host by 愛(ài)奇藝|iQIYI & AVS Workgroup // Prize: NaN
Note: The participants are encouraged to investigate neural network based methods (especially convolutional neural networks) with different network structures, in a hope of achieving the best quality with lightest network configuration for a good tradeoff of efficiency and complexity.
Entry Deadline:
The 2nd Large-scale Video Object Segmentation Challenge
https://youtube-vos.org/challenge/2019/
May. 20 - Sep. 5 2019 // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: As a continuous effort to push forward the research on video object segmentation tasks, we plan to host a second workshop with a challenge based on the YouTube-VOS dataset, targeting at more diversified problem settings, i.e., we plan to provide two challenge tracks in this workshop.
Track 1: Video Object Segmentation
https://youtube-vos.org/dataset/vos/
Track 2: Video Instance Segmentation
https://youtube-vos.org/dataset/vis/
Entry Deadline:
OpenEDS Challenge
https://research.fb.com/programs/openeds-challenge
May 3 - Sep 16, 2019 // Host by EvalAI & Facebook // Prize: $13,000 USD x2
Note: In the absence of accurate gaze labels, we propose to advance the state of the art by carefully designing two challenges that combine human annotation of eye features with unlabeled data. These challenges focus on deeper understanding of the distribution underlying human eye state. We invite ML and CV researchers for participation.
Track-1 Semantic Segmentation challenge
https://evalai.cloudcv.org/web/challenges/challenge-page/353
Track-2 Synthetic Eye Generation challenge
https://evalai.cloudcv.org/web/challenges/challenge-page/354
Entry Deadline:
Exoplanet imaging data challenge
https://exoplanet-imaging-challenge.github.io
May 16th - Sep 16th, 2019 // Host by CodaLab // Prize: NaN
Note: This competition is composed of two sub-challenges focusing on the two most widely used observing techniques: pupil tracking (angular differential imaging, ADI) and multi-spectral imaging combined with pupil tracking (multi-channel spectral differential imaging, ADI+mSDI).
Entry Deadline:
Peking University International Competition on Ocular Disease Intelligent Recognition (ODIR-2019)
https://odir2019.grand-challenge.org/
May 18 - Sep 25, 2019 // Host by Grand Challenges & 北京大學(xué) // Prize: 10,00,000 RMB (140,000+ USD)
Note: 北京大學(xué)'智慧之眼'國(guó)際眼科疾病智能識(shí)別競(jìng)賽
The SG will provide participants with 5,000 structured desensitized ophthalmologic image set of patient's age, sex, binocular color fundus photos and doctors' diagnostic report.
上工醫(yī)信將為參賽者提供5000組包含患者的性別笛辟、年齡功氨、雙眼彩色眼底照片和醫(yī)生印象報(bào)告等的結(jié)構(gòu)化脫敏后眼科的數(shù)據(jù)集。
The purpose of this challenge is to compare approaches of ophthalmic disease classification in color fundus images. Participant will have to submit classification results of eight categories for all the testing data. For every category, a classification probability (value from 0.0 to 1.0) denotes risk of a patient diagnosed with corresponding category.
該競(jìng)賽的目的是比較基于彩色眼底圖像進(jìn)行眼科疾病分類(lèi)的不同方法手幢。 參與者必須提交所有測(cè)試數(shù)據(jù)集的八個(gè)類(lèi)別的分類(lèi)結(jié)果捷凄。 對(duì)于每個(gè)類(lèi)別，分類(lèi)概率（值從0.0到1.0）表示患者被診斷為具有相應(yīng)類(lèi)別的可能性/風(fēng)險(xiǎn)围来。
Entry Deadline:
The 2nd China (Hengqin) International University Quantitative Finance Competition
2019-04-19 至 2020-03-21 // Host by 珠海市橫琴新區(qū)金融服務(wù)中心 // Prize: ￥140萬(wàn)
Note: 第二屆中國(guó)（橫琴）國(guó)際高校量化金融大賽
參賽要求 參賽者應(yīng)根據(jù)題目要求跺涤，完成一篇包括量化金融策略原理、模型的假設(shè)监透、建立和求解桶错、計(jì)算方法的設(shè)計(jì)、分析和檢驗(yàn)胀蛮、模型的改進(jìn)等方面的書(shū)面報(bào)告（即答卷）院刁；并在規(guī)定競(jìng)賽期間內(nèi)，將參賽策略的市場(chǎng)運(yùn)行進(jìn)行模擬仿真競(jìng)賽醇滥。根據(jù)參賽策略的測(cè)試結(jié)果（包括樣本內(nèi)和樣本外）的收益水平及市場(chǎng)風(fēng)險(xiǎn)防范的效果等統(tǒng)一指標(biāo)打分評(píng)比黎比，以市場(chǎng)的標(biāo)準(zhǔn)來(lái)決定優(yōu)劣，評(píng)價(jià)策略的回測(cè)和實(shí)盤(pán)模擬表現(xiàn)鸳玩，同時(shí)考慮策略邏輯的穩(wěn)健性和創(chuàng)新性阅虫。競(jìng)賽評(píng)獎(jiǎng)以策略的合理性、建模的創(chuàng)新性不跟、測(cè)試策略的市場(chǎng)適應(yīng)性及收益風(fēng)險(xiǎn)水平等結(jié)果為主要標(biāo)準(zhǔn)颓帝。
Requirements Participants should write a report covering quantitative financial strategy theories 1) Model theoretical hypothesis and description of quantitive model 2) Data analysis 3) Strategy back testing results and performance analysis. According to the requirements of the competition, participants’ strategies will be back tested and paper traded during the required period. Evaluation and scoring will base on unified measurements including return, volatility, max drawdown of the strategies and so on. The determination of merits and evaluation of strategy back test and paper trading performance will be made according to market standards, while the robustness and innovation of the strategic logic will also be taken into consideration. Key criteria will include the rationality of the strategy, the creativeness of the model, the market adaptability of the testing strategy and the level of return and risk.
Entry Deadline:
Visual Domain Adaptation Challenge (VisDA-2019)
April 9 - Sept. 27, 2019 // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: We are pleased to announce the 2019 Visual Domain Adaptation (VisDA2019) Challenge! It is well known that the success of machine learning methods on visual recognition tasks is highly dependent on access to large labeled datasets. Unfortunately, performance often drops significantly when the model is presented with data from a new deployment domain which it did not see in training, a problem known as dataset shift. The VisDA challenge aims to test domain adaptation methods’ ability to transfer source knowledge and adapt it to novel target domains.
This challenge includes two tracks:
Multi-Source Domain Adaptation Challenge
https://competitions.codalab.org/competitions/22469
Semi-Supervised Domain Adaptation
https://competitions.codalab.org/competitions/22470
Entry Deadline:
Alchemy Contest
5/22 - 9/30, 2019 // Host by CodaLab & Tencent Quantum Lab 騰訊量子實(shí)驗(yàn)室 // Prize: total ￥100,000 RMB
Note: The Tencent Quantum Lab has recently introduced a new molecular dataset, called Alchemy, to facilitate the development of new machine learning models useful for chemistry and materials science.
The dataset lists 12 quantum mechanical properties of 130,000+ organic molecules comprising up to 12 heavy atoms (C, N, O, S, F and Cl), sampled from the GDBMedChem database. These properties have been calculated using the open-source computational chemistry program Python-based Simulation of Chemistry Framework (PySCF).
Entry Deadline:
MicroNet Challenge @NeurIPS 2019
https://micronet-challenge.github.io/
June 1, 2018 - Dec 13, 2019 // Host by NeurIPS 2019 // Prize: NaN
Note: The competition consists of three different tasks. Contestants are free to submit entries for one, two, or all three tasks. Contestants are allowed to enter up to three models for each task, but will be ranked according to their top entry in each task. Entries can only be trained on the training data for the task they are entered in. No pre-training, or use of auxiliary data is allowed.
ImageNet Classification
http://image-net.org/index: The de facto standard dataset for image classification. The dataset is composed of 1,281,167 training images and 50,000 development images. Entries are required to achieve 75% top-1 accuracy on the public test set.
CIFAR-100 Classification
https://www.cs.toronto.edu/~kriz/cifar.html: A widely popular image classification dataset of small images. The dataset is composed of 50,000 training images and 10,000 development images. Entries are required to achieve 80% top-1 accuracy on the test set.
WikiText-103 Language Modeling
https://blog.einstein.ai/the-wikitext-long-term-dependency-language-modeling-dataset/: A language modeling dataset that emphasizes long-term dependencies. Entries will perform the standard language modeling task, predicting the next token from the current one. The dataset is composed of 103 million training words, 217 thousand development words, and 245 thousand testing words. Entries should use the standard word-level vocabulary of 267,735 tokens. Entries are required to achieve a word-level perplexity below 35 on the test set.
Entry Deadline:
Endoscopic Vision Challenge 2019
https://endovis.grand-challenge.org/Endoscopic_Vision_Challenge/
June 5 - Oct 13, 2019 // Host by Grand Challenges // Prize: NaN
Note: As a vision CAI challenge at MICCAI, our aim is to provide a formal framework for evaluating the current state of the art, gather researchers in the field and provide high quality data with protocols for validating endoscopic vision algorithms.
EndoVis 2019 Sub-challenges:
Surgical Workflow and Skill Analysis
https://endovissub-workflowandskill.grand-challenge.org
Stereo Correspondence and Reconstruction of Endoscopic Data
https://endovissub2019-scared.grand-challenge.org
Entry Deadline:
Graph Golf: The Order/degree Problem Competition
http://research.nii.ac.jp/graphgolf/
05-13 ~ 11-26, 2019 // Host by CodaLab & CANDAR 2019 // Prize: NaN
Note: Find a graph that has smallest diameter & average shortest path length given an order and a degree.
Graph Golf is an international competition of the order/degree problem since 2015. It is conducted with the goal of making a catalog of smallest-diameter graphs for every order/degree pair. Anyone in the world can take part in the competition by submitting a graph. Outstanding authors are awarded in CANDAR 2019, an international conference held in Nagasaki, Japan, in November 2019.
Entry Deadline:
The Animal-AI Olympics
April - December 2019 // Host by NeurIPS 2019 // Prize: $10,000+
Note: 基于Unity ML Agents Toolkit的動(dòng)物認(rèn)知-AI 挑戰(zhàn)
This competition pits our best AI approaches against the animal kingdom to determine if the great successes of AI are now ready to compete with the great successes of evolution at their own game.
Entry Deadline:
Geopolitical Forecasting [GF] Challenge 2
https://www.herox.com/IARPAGFChallenge2
April 4, 2018 - Feb. 1, 2020 // Host by Herox // Prize: $250,000
Note: Solvers, whether individuals or teams, will create innovative solutions and methods to produce forecasts to a set of more than 300 questions referred to as Individual Forecasting Problems (IFPs), released regularly over the course of the nine-month Challenge.
Entry Deadline:
ModaNet Fashion Understanding Challenge
https://evalai.cloudcv.org/web/challenges/challenge-page/151
Oct 1, 2018 - Dec 11, 2019 // Host by EvalAI // Prize: NaN
Note: In this challenge, we evaluate model performance for three tasks, object detection, semantic segmentation and instance segmentation. You can participate all tasks or any one of them by choosing which results to be included in your submission.
Entry Deadline:
「二分類(lèi)算法」提供銀行精準(zhǔn)營(yíng)銷(xiāo)解決方案 | 練習(xí)賽
https://www.kesci.com/home/competition/5c234c6626ba91002bfdfdd3
2018年12月29日 - 2019年12月29日 // Host by Kesci // Prize: NaN
Note: 本練習(xí)賽的數(shù)據(jù)，選自UCI機(jī)器學(xué)習(xí)庫(kù)中的「銀行營(yíng)銷(xiāo)數(shù)據(jù)集(Bank Marketing Data Set)」
Entry Deadline:
SPIE-AAPM-NCI BreastPathQ: Cancer Cellularity Challenge 2019
http://spiechallenges.cloudapp.net/competitions/14
Oct. 15, 2018 - Dec. 31, 2019 // Host by ISBI 2019 & Grand Challenges & cloudapp.net // Prize: NaN
Note: Participants will be tasked to develop an automated method for analyzing histology patches extracted from whole slide images and assign a score reflecting cancer cellularity in each.
Entry Deadline:
Optimizing well-being at work
https://challengedata.ens.fr/challenges/15
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Oze Energies // Prize: NaN
Note: This challenge proposes to develop machine learning based approaches so as to predict individuals' comfort model using several time series of environmental data obtained from sensors in a large building. The objective is to learn a classifier that uses these time series as inputs to predict the associated comfort class computed as an average of the comfort classes of all individuals in the building, assumed to experience the same environmental conditions.
Entry Deadline:
Drug-related questions classification
https://challengedata.ens.fr/challenges/17
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Posos // Prize: NaN
Note: The goal of Posos challenge is to predict for each question the associated intent.
Entry Deadline:
Detecting breast cancer metastases
https://challengedata.ens.fr/challenges/18
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & OWKIN // Prize: NaN
Note: The challenge proposed by Owkin is a weakly-supervised binary classification problem : predict whether a patient has any metastase in its lymph node or not, given its slide.
Entry Deadline:
Building Claim Prediction
https://challengedata.ens.fr/challenges/19
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Generali // Prize: NaN
Note: The goal of the challenge is to predict if a building will have an insurance claim during a certain period. You will have to predict a probability of having at least one claim over the insured period of a building.
Entry Deadline:
Crack the neural code of the brain
https://challengedata.ens.fr/challenges/14
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & GNT ENS // Prize: NaN
Note: The challenge goal is to classify the brain activity state of an animal based on spiking activity patterns of its individual neurons.
Entry Deadline:
Prediction of Sharpe ratio for blends of quantitative strategies
https://challengedata.ens.fr/challenges/13
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Napoleon X // Prize: NaN
Note: The problem is a prediction challenge that aims at helping the Company to build an optimal blend of quantitative strategies, given a set of such strategies.
Entry Deadline:
Historical consumption regression for electricity supply pricing
https://challengedata.ens.fr/challenges/12
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & BCM Energy // Prize: NaN
Note: The goal of the challenge is to predict, based on the analysis of the correlation of a year of consumption and weather training data, the electricity consumption of two given sites for a test year.
Entry Deadline:
Predict brain deep sleep slow oscillation
https://challengedata.ens.fr/challenges/10
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Dreem // Prize: NaN
Note: In this dataset, we try to predict whether or not a slow oscillation will be followed by another one in sham condition, i.e. without any stimulation.
Entry Deadline:
Spatiotemporal PM10 concentration prediction
https://challengedata.ens.fr/challenges/7
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Plume Labs // Prize: NaN
Note: In order to provide air quality forecasts, Plume Labs has built a unique database with readings collected by monitoring stations all over the world. The problem we submit consists in predicting the PM10 readings of some air quality monitoring stations using the readings provided by the monitoring stations nearby as well as urban features.
Entry Deadline:
Dynamic Profile Forecasting
https://challengedata.ens.fr/challenges/6
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Enedis // Prize: NaN
Note: This challenge is about forecasting dynamic profiles values from their past values and all the components of Enedis’ Half hourly Electrical Balancing.
Entry Deadline:
Solve 2x2x2 Rubik's cube
https://challengedata.ens.fr/challenges/20
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & LumenAI // Prize: NaN
Note: The goal is to design an automatic Rubik's analyzer that estimates the current length of the shortest path to the solution.
Entry Deadline:
Exotic pricing with multidimensional non-linear interpolation
https://challengedata.ens.fr/challenges/9
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Natixis // Prize: NaN
Note: The purpose of the challenge is to use a training set of 1 million prices to learn how to price a specific type of instruments described by 23 parameters by nonlinear interpolation on these prices.
Entry Deadline:
Screening and Diagnosis of esophageal cancer from in-vivo microscopy images
https://challengedata.ens.fr/challenges/11
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & Mauna Kea Technologies // Prize: NaN
Note: The goal of this challenge is to build an image classifier to assist physicians in the screening and diagnosis of esophageal cancer.
Entry Deadline:
Prediction of daily stock movements on the US market
https://challengedata.ens.fr/challenges/16
Jan. 1, 2019 - Jan. 1, 2020 // Host by Challenge data & CFM // Prize: NaN
Note: The goal of this challenge is to predict the sign of the returns (= price change over some time interval) at the end of about 700 days for about 700 stocks.
Entry Deadline:
MEMENTO: MRI White Matter Reconstruction
https://my.vanderbilt.edu/memento/
March 7, 2019 - March 4, 2020 // Host by ISBI 2019 // Prize: NaN
Note: This will be a 2-year challenge.
We aim to host 3 sub-challenges evaluating our current ability to:
(1) predict unseen signal (signal representation; sub-challenge #1)
(2) estimate microstructural measures (signal modeling; sub-challenge #2)
(3) evaluate sensitivity and specificity of potential biomarkers (biomarker evaluation; sub-challenge #3).
Entry Deadline:
Propensity to Fund Mortgages
https://www.crowdanalytix.com/contests/propensity-to-fund-mortgages
25 APR 2019 - 6 JUN 2019 // Host by CrowdANALYTIX // Prize: $10000
Note: Develop a model to predict, given mortgage application information, whether the mortgage will be funded or not.
To predict whether a mortgage will be funded using only this application data, certain leading factors driving the loan’s ultimate status will be identified. Solvers will discover the specific aspects of the dataset that have the greatest impact, and build a model based on this information.
Entry Deadline:
Identify Characters from Product Images
https://www.crowdanalytix.com/contests/identify-characters-from-product-images
12 MAY 2019 - 9 JUL 2019 // Host by CrowdANALYTIX // Prize: NaN
Note: Identify the characters from product image from a list of 42 possible values.
While using machine learning to perform image recognition is currently one of the most popular use cases, in some cases, the existing large-scale models are too broad to be effective for specific business use cases. In this contest we will use a data driven approach to identify the “characters” in an image (product images).
Entry Deadline:
KiTS19 Challenge
https://kits19.grand-challenge.org
March 15 - August 2, 2019 // Host by Grand Challenges // Prize: NaN
Note: The goal of this challenge is to accelerate the development of reliable kidney and kidney tumor semantic segmentation methodologies.
Entry Deadline:
PAIP 2019 Challenge
https://paip2019.grand-challenge.org
April 15 - September 2, 2019 // Host by Grand Challenges & MICCAI 2019 // Prize: NaN
Note: The goal of the challenge is to evaluate new and existing algorithms for automated detection of liver cancer in whole-slide images (WSIs). There are two tasks and therefore two leaderboards for evaluating the performance of the algorithms. Participants can choose to join both or either tasks according to their interests.
Task 1: Liver Cancer Segmentation
Task 2: Viable Tumor Burden Estimation
Entry Deadline:
ImageNet Object Localization Challenge
https://www.kaggle.com/c/imagenet-object-localization-challenge
Now - December 31 2029 // Host by Kaggle // Prize: NaN
Note: Identify the objects in images
Entry Deadline:
nocaps
Feb 8, 2019 - Apr 26, 2099 // Host by EvalAI // Prize: NaN
Note: Image captioning models have achieved impressive results on datasets containing limited visual concepts and large amounts of paired image-caption training data. However, if these models are to ever function in the wild, a much larger variety of visual concepts must be learned, ideally from less supervision. To encourage the development of image captioning models that can learn visual concepts from alternative data sources, such as object detection datasets, we present the first large-scale benchmark for this task. Dubbed nocaps, for novel object captioning at scale, our benchmark consists of 166,100 human-generated captions describing 15,100 images from the Open Images validation and test sets. The associated training data consists of COCO image-caption pairs, plus Open Images imagelevel labels and object bounding boxes. Since Open Images contains many more classes than COCO, nearly 400 object classes seen in test images have no or very few associated training captions (hence, nocaps). We extend existing novel object captioning models to establish strong baselines for this benchmark and provide analysis to guide future work on this task.
Entry Deadline:
nuScenes detection challenge
Apr 1, 2019 - Jan 1, 2099 // Host by EvalAI & CVPR 2019 // Prize: NaN
Note: The nuScenes dataset is a large-scale autonomous driving dataset.
Entry Deadline:
Predict Future Sales
https://www.kaggle.com/c/competitive-data-science-predict-future-sales
No deadline // Host by Kaggle // Prize: NaN
Note: Final project for "How to win a data science competition" Coursera course
No Deadline.
Evaluating grammatical error corrections
https://competitions.codalab.org/competitions/15475
Nov. 23, 2016 - Never // Host by CodaLab // Prize: NaN
No Deadline.
Challenge: Learning To Drive (L2D)
https://competitions.codalab.org/competitions/23245
June 1, 2019 - Never // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: Challenge participants need to develop driving models that can drive most similar to the human driver that recorded the dataset.
No Deadline.
Challenge: Learning To Drive (L2D)
https://competitions.codalab.org/competitions/23245
June 1, 2019 - Never // Host by CodaLab & ICCV 2019 // Prize: NaN
Note: Challenge participants need to develop driving models that can drive most similar to the human driver that recorded the dataset.
No Deadline.
Mobile age group classification
https://competitions.codalab.org/competitions/22946
May. 17, 2019 - Never // Host by CodaLab // Prize: NaN
Note: This is an EE331 competition leaderboard for Mobile age group classification. It consists of 157K datasamples with 85 various features and age group label (ranging from 1 to 6). The data is splitted into train : validation : test sset with 70 : 20 : 10 ratio.
No Deadline.
Perfect Pitching Simulator
https://fastballs.wordpress.com/category/pitchfx-glossary/
May. 17, 2019 - Never // Host by CodaLab // Prize: NaN
Note: Perfect Pitching Simulator!
No Deadline.
ActivityNet-Entities Object Localization Task
https://github.com/facebookresearch/ActivityNet-Entities
May 7, 2019 - Never // Host by CodaLab & CVPR 2019 // Prize: NaN
Note: ActivityNet-Entities, is based on the video description dataset ActivityNet Captions and augments it with 158k bounding box annotations, each grounding a noun phrase (NP). Here we release the complete set of NP-based annotations as well as the pre-processed object-based annotations.
please see our dataset repo, code repo, and CVPR 2019 oral paper.
No Deadline.
YouCook2 Dense Video Captioning
http://youcook2.eecs.umich.edu
May 6, 2019 - Never // Host by CodaLab // Prize: NaN
Note: YouCook2 is currently suitable for video-language research, weakly-supervised activity and object recognition in video, common object and action discovery across videos and procedure learning.
No Deadline.
The First Australian Centre for Robotic Vision (ACRV) Challenge
https://competitions.codalab.org/competitions/20940
Dec. 1, 2018 - Never // Host by CodaLab // Prize: NaN
Note: The challenge consists in building an AI agent that can play efficiently and win simplified text-based games using TextWorld.
No Deadline.
TVQA Test Public Evaluation (w/timestamp) Beta
https://competitions.codalab.org/competitions/20686
Nov. 16, 2018 - Never // Host by CodaLab & TVQA // Prize: NaN
Note: This portal is only used for models that used 'ts' (timestamp annotations)
TVQA is a large-scale video QA dataset based on 6 popular TV shows (Friends, The Big Bang Theory, How I Met Your Mother, House M.D., Grey's Anatomy, Castle).
No Deadline.
IWCS-2019 shared task: DRS Parsing
https://competitions.codalab.org/competitions/20220
Feb. 25, 2018 - Never // Host by CodaLab & IWCS-2019 // Prize: NaN
Note: The shared task on DRS parsing will be co-located with IWCS-2019 held in Gothenburg, Sweden on 23-27 May.
No Deadline.
Intuitive Physics Challenge 2019
https://competitions.codalab.org/competitions/20574
Oct. 1, 2018 - Never // Host by CodaLab & IntPhys // Prize: NaN
No Deadline.
SemEval-2019
http://alt.qcri.org/semeval2019/index.php?id=tasks
Now - Never // Host by CodaLab & SemEval-2019 // Prize: NaN
Note:
Frame semantics and semantic parsing:
Task 1: Cross-lingual Semantic Parsing with UCCA
https://competitions.codalab.org/competitions/19160
Task 2: Unsupervised Lexical Semantic Frame Induction
https://competitions.codalab.org/competitions/19159
Opinion, emotion and abusive language detection
Task 3: EmoContext: Contextual Emotion Detection in Text
https://www.humanizing-ai.com/emocontext.html
Task 4: Hyperpartisan News Detection
http://www.webis.de/events/semeval-19
Task 5: HatEval: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
https://competitions.codalab.org/competitions/19935
Task 6: OffensEval: Identifying and Categorizing Offensive Language in Social Media<\a>
Fact vs fiction
Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours
Task 8: Fact Checking in Community Question Answering Forums
https://competitions.codalab.org/competitions/20022
Information extraction and question answering
Task 9: Suggestion Mining from Online Reviews and Forums
https://competitions.codalab.org/competitions/19955
Task 10: Math Question Answering
https://competitions.codalab.org/competitions/20013
NLP for scientific applications
Task 12: Toponym Resolution in Scientific Papers
https://competitions.codalab.org/competitions/19948
No Deadline.
WiC_competition
https://competitions.codalab.org/competitions/20010
Aug. 18, 2018 - Never // Host by CodaLab // Prize: NaN
Note: You can get all the information and data at https://pilehvar.github.io/wic
No Deadline.
EPIC-Kitchens Action Anticipation
https://competitions.codalab.org/competitions/20115
Aug. 1, 2018 - Never // Host by CodaLab & EPIC-KITCHENS 2018 // Prize: NaN
Note: The largest dataset in first-person (egocentric) vision; multi-faceted non-scripted recordings in native environments - i.e. the wearers' homes, capturing all daily activities in the kitchen over multiple days.
Action-Recognition Challenge
https://competitions.codalab.org/competitions/20115
Action-Anticipation Challenge
https://competitions.codalab.org/competitions/20071
Object-Detection Challenge
https://competitions.codalab.org/competitions/20111
No Deadline.
OxUvA Long-Term Tracking Challenge
https://competitions.codalab.org/competitions/19529
July 1, 2018 - Never // Host by CodaLab & ECCV 2018 // Prize: NaN
Note: "We introduce a new video dataset and benchmark to assess single-object tracking algorithms."
No Deadline.
Lymphocyte Detection
https://lyon19.grand-challenge.org
under construction // Host by Grand Challenges // Prize: NaN
Note: Dataset contains manual annotations as a ground truth data.
No Deadline.
DRIVE: Digital Retinal Images for Vessel Extraction
https://drive.grand-challenge.org
No deadline // Host by Grand Challenges // Prize: NaN
Note: The DRIVE database has been established to enable comparative studies on segmentation of blood vessels in retinal images. Develop a system to automatically segment vessels in human retina fundus images.
No Deadline.
PatchCamelyon
https://github.com/basveeling/pcam
No deadline // Host by Grand Challenges // Prize: NaN
Note: The PatchCamelyon benchmark is a new and challenging image classification dataset. It consists of 327.680 color images (96 x 96px) extracted from histopathologic scans of lymph node sections. Each image is annoted with a binary label indicating presence of metastatic tissue. PCam provides a new benchmark for machine learning models: bigger than CIFAR10, smaller than imagenet, trainable on a single GPU.
No Deadline.
The Large Scale Vertebrae Segmentation Challenge (VerSe2019)
https://verse2019.grand-challenge.org
May 16 - TBA // Host by Grand Challenges // Prize: NaN
Note: Spine or vertebral segmentation is a crucial step in all applications regarding automated quantification of spinal morphology and pathology. With the advent of deep learning, for such a task on computed tomography (CT) scans, a big and varied data is a primary sought-after resource.
Task 1: Vertebra Labelling
Task 2: Vertebra Segmentation
No Deadline.
Vision and Language Navigation
https://evalai.cloudcv.org/web/challenges/challenge-page/97
Mar 13, 2018 - Dec 31, 2099 // Host by EvalAI // Prize: NaN
Note: The challenge requires an autonomous agent to follow a natural language navigation instruction to navigate to a goal location in a previously unseen real-world building.
No Deadline.
VizWiz Challenge 2018
http://vizwiz.org/data/#challenge
Jun 20, 2018 - Jun 22, 2100 // Host by EvalAI // Prize: NaN
Note: Our proposed challenge addresses the following two tasks for this dataset: (1) predict the answer to a visual question and (2) predict whether a visual question cannot be answered.
No Deadline.
SQuAD2.0: The Stanford Question Answering Dataset
https://rajpurkar.github.io/SQuAD-explorer/
No deadline // Host by Stanford NLP Group // Prize: NaN
Note: Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
No Deadline.
CoQA: A Conversational Question Answering Challenge
https://stanfordnlp.github.io/coqa/
No deadline // Host by Stanford NLP Group // Prize: NaN
Note: CoQA is a large-scale dataset for building Conversational Question Answering systems. The goal of the CoQA challenge is to measure the ability of machines to understand a text passage and answer a series of interconnected questions that appear in a conversation. CoQA is pronounced as coca.
No Deadline.
Unrestricted Adversarial Examples Challenge
https://github.com/google/unrestricted-adversarial-examples
No deadline // Host by Google AI // Prize: NaN
Note: A community-based challenge to incentivize and measure progress towards the goal of zero confident classification errors in machine learning models.
(不受限對(duì)抗樣本挑戰(zhàn)) The project on Github
No Deadline.
The Natural Language Decathlon: A Multitask Challenge for NLP
No deadline // Host by salesforce // Prize: NaN
Note: The Natural Language Decathlon is a multitask challenge that spans ten tasks: question answering (SQuAD), machine translation (IWSLT), summarization (CNN/DM), natural language inference (MNLI), sentiment analysis (SST), semantic role labeling(QA?SRL), zero-shot relation extraction (QA?ZRE), goal-oriented dialogue (WOZ), semantic parsing (WikiSQL), and commonsense reasoning (MWSC).
