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Submitted URL: http://cocodataset.org/
Effective URL: https://cocodataset.org/
Submission: On June 30 via api from US — Scanned from DE
Effective URL: https://cocodataset.org/
Submission: On June 30 via api from US — Scanned from DE
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info@cocodataset.org * Home * People * Dataset * Overview * Explore * Download * External * Terms of Use * Tasks * Detection 2020 * Keypoints 2020 * Panoptic 2020 * DensePose 2020 * * Detection 2019 * Keypoints 2019 * Stuff 2019 * Panoptic 2019 * * Detection 2018 * Keypoints 2018 * Stuff 2018 * Panoptic 2018 * * Detection 2017 * Keypoints 2017 * Stuff 2017 * * Detection 2016 * Keypoints 2016 * * Detection 2015 * Captioning 2015 * Evaluate * Participate: * Data Format * Results Format * Test Guidelines * Upload Results * * Evaluate: * Detection * Keypoints * Stuff * Panoptic * DensePose * Captions * * Leaderboards: * Detection * Keypoints * Stuff * Panoptic * Captions NEWS * We are pleased to announce the LVIS 2021 Challenge and Workshop to be held at ICCV. * Please note that there will not be a COCO 2021 Challenge, instead, we encourage people to participate in the LVIS 2021 Challenge. * We have partnered with the team behind the open-source tool FiftyOne to make it easier to download, visualize, and evaluate COCO * FiftyOne is an open-source tool facilitating visualization and access to COCO data resources and serves as an evaluation tool for model analysis on COCO. WHAT IS COCO? COCO is a large-scale object detection, segmentation, and captioning dataset. COCO has several features: * Object segmentation * Recognition in context * Superpixel stuff segmentation * 330K images (>200K labeled) * 1.5 million object instances * 80 object categories * 91 stuff categories * 5 captions per image * 250,000 people with keypoints COLLABORATORS Tsung-Yi Lin Google Brain Genevieve Patterson MSR, Trash TV Matteo R. Ronchi Caltech Yin Cui Google Michael Maire TTI-Chicago Serge Belongie Cornell Tech Lubomir Bourdev WaveOne, Inc. Ross Girshick FAIR James Hays Georgia Tech Pietro Perona Caltech Deva Ramanan CMU Larry Zitnick FAIR Piotr Dollár FAIR SPONSORS Github Page Source Terms of Use