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readme.md

ECCV 2018 PoseTrack DensePose Task

PoseTrack DensePose Splash Image

Overview

The PoseTrack DensePose Task requires dense estimation of human pose through time in challenging, uncontrolled conditions. The task involves processing video frames to simultaneously detect people, segment their bodies and map all image pixels that belong to a human body to the 3D surface of the body. For full details on this task please see the evaluation page.

This task is part of the PoseTrack Challenge Workshop at ECCV 2018. For further details about the workshop please visit the workshop page. Please also see the related PoseTrack Articulated Human Pose Estimation and Tracking and 3D Human Pose Estimation tasks.

The PoseTrack DensePose train, validation, and test sets, containing more than 5,000 images and 27,000 person instances labeled with DensePose annotations are available for download. Annotations on train and val with over 13,000 people are publicly available.

Evaluation server for the 2018 task is open.

Dates

August 18, 2018 Submission deadline (23:59 PST)
September 2, 2018 Challenge winners notified
September 8, 2018 Winners present at ECCV 2018 Workshop

Organizers

Riza Alp Güler (INRIA, CentraleSupélec)

Natalia Neverova (Facebook AI Research)

Iasonas Kokkinos (Facebook AI Research)

Task Guidelines

Participants are recommended but not restricted to train their algorithms on PoseTrack DensePose train and val sets. The download page has links to the image data. When participating in this task, please specify any and all external data used for training in the "method description" when uploading results to the evaluation server. Listing external data used is mandatory. We emphasize that any form of annotation or use of the test sets for supervised or unsupervised training is strictly forbidden. A more thorough explanation of all these details is available on the upload page, please be sure to review it carefully prior to participating. Results in the correct format must be uploaded to the evaluation server. The evaluation page lists detailed information regarding how results will be evaluated. Challenge participants with the most successful and innovative methods will be invited to present at the workshop.

Tools and Instructions

We provide extensive API support for the images, annotations, and evaluation code. To download the COCO DensePose API, please visit our GitHub repository. Due to the complexity of this task, the process of participating may not seem simple. To help, we provide explanations and instructions for each step of the process: download, data format, results format, upload and evaluation pages.

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