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http://mscoco.org Ross Girshick Microsoft Research Tsung-Yi Lin Cornell Tech Michael Maire TTI Chicago Serge Belongie Cornell Tech Lubomir Bourdev Facebook James Hays Brown University Pietro Perona Caltech Deva Ramanan UC Irvine Piotr Dollar Microsoft Research Larry Zitnick Microsoft Research

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http://mscoco.org

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Instance segmentation Non-iconic Images

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http://mscoco.org Non-iconic images

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http://mscoco.org

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Sentences Beyond detection Collecting Image Annotations Using Amazons Mechanical Turk, C. Rashtchian, P. Young, M. Hodosh, J. Hockenmaier, NAACL HLT Workshop on Creating Speech and Language Data with Amazons Mechanical Turk, 2010

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http://mscoco.org Beyond detection Keypoints (provided by Facebook)

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http://mscoco.org

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MS COCO 2014 release (half of COCO) 160k images 80 object categories (things not stuff) 1M+ instances (300k people) Every instance segmented 5 sentences per image Separate train and validation set Over 77,000 worker hours (8+ years)

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http://mscoco.org MS COCO 2015 (full release) http://mscoco.org Early 2015 80-100 object categories 330k images 2M+ instances (700k people) Every instance segmented 5 sentences per image Keypoint annotations

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http://mscoco.org

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Algorithm Evaluation Still debating The metric should be: Simple Relevant Robust IoU on the segmentations Small objects % contour Scores that work for bboxes and segmentations Types of instances? Leaderboard Challenge?

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http://mscoco.org Visit mscoco.org Ross Girshick Microsoft Research Tsung-Yi Lin Cornell Tech Michael Maire TTI Chicago Serge Belongie Cornell Tech Lubomir Bourdev Facebook James Hays Brown University Pietro Perona Caltech Deva Ramanan UC Irvine Piotr Dollar Microsoft Research Larry Zitnick Microsoft Research