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 state of the art in object detection forward. Teams are encouraged to compete in either (or both) of two object detection challenges: using bounding box output or object segmentation output. For full details of this task please see the COCO Detection Challenge page.

2.2. COCO Keypoint Challenge

The COCO 2017 Keypoint Challenge requires localization of person keypoints in challenging, uncontrolled conditions. The keypoint challenge involves simultaneously detecting people and localizing their keypoints (person locations are not given at test time). For full details of this task please see the COCO Keypoints Challenge page.

2.3. COCO Stuff Challenge

The COCO 2017 Stuff Segmentation Challenge is designed to push the state of the art in semantic segmentation of stuff classes. Whereas the COCO 2017 Detection Challenge addresses thing classes (person, car, elephant), this challenge focuses on stuff classes (grass, wall, sky). For full details of this task please see the COCO Stuff Challenge page.

3. Places Challenges

The Places Challenge will host three tracks meant to complement the COCO Challenges. The data for the 2017 Places Challenge is from the pixel-wise annotated image dataset ADE20K, in which there are 20K images for training, 2K validation images, and 3K testing images. The three specific tracks in the Places Challenge 2017 are: (1) scene parsing, (2) instance segmentation, and (3) semantic boundary detection. See the Places Challenge Page for detailed information.

4. Challenge Dates

5. Workshop Schedule - 10.29.2017

8:50	Opening Comments
9:00	Detection Challenge Track	Tsung-Yi Lin (Cornell Tech, Google Research)	Talk
9:10	Detection/Segmentation/Places Competitor	Team Megvii (Face++)	Talk
9:30	Detection/Segmentation Competitor	Team UCenter (CUHK & Peking University)	Talk
9:50	Detection/Segmentation Competitor	Team MSRA	Talk
10:00	Detection/Segmentation Competitor	Team FAIR	Talk
10:10	Morning Break: Coffee + Posters
10:40	Keypoints Challenge Track	Matteo Ronchi (Caltech)	Talk
10:50	Keypoints Competitor	Team Megvii (Face++)	Talk
11:05	Keypoints Competitor	Team OKS (Beihang University & SenseTime)	Talk
11:20	Stuff Challenge Track	Holger Caesar (University of Edinburgh)	Talk
11:30	Stuff Competitor	Team FAIR	Talk
11:45	Stuff Competitor	Team Oxford Active Vision Lab	——
12:00	Invited Talk	Vladlen Koltun (Intel Labs)	Talk
12:30	Lunch
14:00	Invited Talk	Genevieve Patterson (MSR NE)	Talk
14:15	Invited Talk	Alexander Kirillov (University of Heidelberg & FAIR)	Talk
14:30	Places Challenge Track	Bolei Zhou (MIT), Hang Zhao (MIT)	Talk
14:45	Places Competitor	Team G-RMI (Google Research)	Talk
15:05	Places Competitor	Team WinterIsComing (ByteDance)	Talk
15:25	Places Competitor	Team CASIA_IVA_JD (Institute of Automation, Chinese Academy of Sciences, & JD)	Talk
15:45	Afternoon Break: Coffee + Posters
16:15	Discussion Panel	Genevieve Patterson (MSR NE), Hang Zhao (MIT)

6. Challenge Winners

For details on the winning entries please see the track overview slides and individual talks linked in the schedule.

	1st place	2nd place	3rd place	4th place
COCO Detection: Bounding Box	Megvii	UCenter	MSRA	FAIR
COCO Detection: Segmentation	UCenter	Megvii	FAIR	MSRA
COCO Keypoints	Megvii	Oks	Bangbangren	—
COCO Stuff	FAIR	G-RMI	Oxford	—
Places Instance Segmentation	Megvii	G-RMI	BlueSky	—
Places Scene Parsing	CASIA_IVA_JD	WinterIsComing	xdliang	—

7. Invited Speakers