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20 | 20 | prize: NaN
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21 | 21 |
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22 | 22 |
|
| 23 | +- id: TweetQA |
| 24 | + type1: |
| 25 | + - PF |
| 26 | + - AC |
| 27 | + type2: |
| 28 | + - NLP |
| 29 | + title: TweetQA Competition |
| 30 | + url: https://tweetqa.github.io |
| 31 | + hostby: |
| 32 | + - CodaLab: https://competitions.codalab.org/competitions/20307 |
| 33 | + range: July 20, 2019 - Never |
| 34 | + deadtime: 'No deadline' |
| 35 | + timezone: UTC |
| 36 | + pubtime: '2019-07-23' |
| 37 | + note: 'Unlike other QA datasets like SQuAD in which the answers are extractive, we allow the answers to be abstractive. The task requires model to read a short tweet and a question and outputs a text phrase (does not need to be in the tweet) as the answer.' |
| 38 | + prize: NaN |
| 39 | + |
| 40 | + |
| 41 | + |
| 42 | +- id: AIM2019 |
| 43 | + type1: |
| 44 | + - PF |
| 45 | + - AC |
| 46 | + type2: |
| 47 | + - CV |
| 48 | + title: 'AIM 2019 image manipulation challenges' |
| 49 | + url: http://www.vision.ee.ethz.ch/aim19/ |
| 50 | + hostby: |
| 51 | + - CodaLab: https://competitions.codalab.org/ |
| 52 | + - ICCV 2019: http://iccv2019.thecvf.com |
| 53 | + range: July 17, 2019 - Aug. 30, 2019 |
| 54 | + deadtime: "2019-08-23 23:59:59" |
| 55 | + timezone: UTC |
| 56 | + pubtime: '2019-07-23' |
| 57 | + note: 'Advances in Image Manipulation workshop and challenges on image and video manipulation in conjunction with ICCV 2019. |
| 58 | + <br>AIM 2019 image manipulation challenges: |
| 59 | + <br><a href="https://competitions.codalab.org/competitions/20156">Bokeh Effect Challenge: Track 1 Fidelity</a>; |
| 60 | + <br><a href="https://competitions.codalab.org/competitions/20157">Bokeh Effect Challenge: Track 2 Perceptual</a>; |
| 61 | + <br><a href="https://competitions.codalab.org/competitions/20158">RAW-to-RGB Mapping Challenge: Track 1 Fidelity</a>; |
| 62 | + <br><a href="https://competitions.codalab.org/competitions/20159">RAW-to-RGB Mapping Challenge: Track 2 Perceptual</a>; |
| 63 | + <br><a href="https://competitions.codalab.org/competitions/20163">Real World Super-Resolution Challenge: Track 1 Same Domain</a>; |
| 64 | + <br><a href="https://competitions.codalab.org/competitions/20164">Real World Super-Resolution Challenge: Track 2 Target Domain</a>; |
| 65 | + <br><a href="https://competitions.codalab.org/competitions/20165">Demoireing Challenge: Track 1 Fidelity</a>; |
| 66 | + <br><a href="https://competitions.codalab.org/competitions/20166">Demoireing Challenge: Track 2 Perceptual</a>; |
| 67 | + <br><a href="https://competitions.codalab.org/competitions/20167">Constrained Super-Resolution Challenge: Track 1 Parameters optimization</a>; |
| 68 | + <br><a href="https://competitions.codalab.org/competitions/20168">Constrained Super-Resolution Challenge: Track 2 Inference optimization</a>; |
| 69 | + <br><a href="https://competitions.codalab.org/competitions/20169">Constrained Super-Resolution Challenge: Track 3 Fidelity optimization</a>; |
| 70 | + <br><a href="https://competitions.codalab.org/competitions/20235">Extreme Super-Resolution Challenge: Track 1 Fidelity</a>; |
| 71 | + <br><a href="https://competitions.codalab.org/competitions/20236">Extreme Super-Resolution Challenge: Track 2 Perceptual</a>; |
| 72 | + <br>AIM 2019 video manipulation challenges: |
| 73 | + <br><a href="https://competitions.codalab.org/competitions/20246">Video Quality Mapping Challenge : Track 1 Supervised</a>; |
| 74 | + <br><a href="https://competitions.codalab.org/competitions/20247">Video Quality Mapping Challenge : Track 2 Unsupervised</a>; |
| 75 | + <br><a href="https://competitions.codalab.org/competitions/20248">Video Extreme Super-Resolution Challenge: Track 1 Fidelity</a>; |
| 76 | + <br><a href="https://competitions.codalab.org/competitions/20249">Video Extreme Super-Resolution Challenge: Track 2 Perceptual</a>; |
| 77 | + <br><a href="https://competitions.codalab.org/competitions/20244">Video Temporal Super-Resolution Challenge</a>; |
| 78 | + ' |
| 79 | + prize: NaN |
| 80 | + |
| 81 | + |
| 82 | +- id: VoxCeleb |
| 83 | + type1: |
| 84 | + - PF |
| 85 | + - AC |
| 86 | + type2: |
| 87 | + - SP |
| 88 | + - CV |
| 89 | + title: The VoxCeleb Speaker Recognition Challenge |
| 90 | + url: http://www.robots.ox.ac.uk/~vgg/data/voxceleb/competition.html |
| 91 | + hostby: |
| 92 | + - CodaLab: https://competitions.codalab.org/competitions/20199 |
| 93 | + range: July 15, 2019 - Sep. 14, 2019 |
| 94 | + deadtime: "2019-08-15 23:59:59" |
| 95 | + timezone: UTC |
| 96 | + pubtime: '2019-07-23' |
| 97 | + note: "The goal of this challenge is to probe how well current methods can recognize speakers from speech obtained 'in the wild'. The challenge will consists of the following two tasks: |
| 98 | + <br>Audio only speaker verification - Fixed training data: This task requires that participants train only on the VoxCeleb2 dev dataset for which we have already released speaker verification labels. The dev dataset contains 1,092,009 utterances from 5,994 speakers. |
| 99 | + <br>Audio only speaker verification - Open training data: For the open training condition, participants can use the VoxCeleb datasets and any other data (including that which is not publicly released) except the challenge's test data" |
| 100 | + prize: NaN |
23 | 101 |
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24 | 102 | - id: Reconstruction2D3D
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25 | 103 | type1:
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