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raw text

COCO + Places 2017 | ICCV 2017 COCO + Places 2017 Joint Workshop of the COCO and Places Challenges at ICCV 2017 1. Overview The goal of the joint COCO and Places Challenge is to study object recognition in the context of scene understanding. Competition winners have been announced, for additional details see the workshop schedule . 2. COCO Challenges COCO is an image dataset designed to spur object detection research with a focus on detecting objects in context. The annotations include pixel-level segmentation of object belonging to 80 categories, keypoint annotations for person instances, stuff segmentations for 91 categories, and five image captions per image. The specific tracks in the COCO 2017 Challenges are (1) object detection with bounding boxes and segmentation masks, (2) joint detection and person keypoint estimation, and (3) stuff segmentation. We describe each next. 2.1. COCO Detection Challenge The COCO 2017 Detection Challenge is designed to push the...

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