ACM SIGCHI General Interest Announcements (Mailing List)


Options: Use Forum View

Use Monospaced Font
Show Text Part by Default
Show All Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Meysam Madadi <[log in to unmask]>
Reply To:
Meysam Madadi <[log in to unmask]>
Wed, 13 May 2020 15:54:10 +0200
text/plain (139 lines)
Dear colleague,

We are happy to announce the starting of our NeurIPS 2020 3D + texture
garment reconstruction competition. Sorry for multiple copies.

What is the competition about?

Humans are important targets in many applications. Accurately tracking,
capturing, reconstructing and animating the human body, face and garments
in 3D are critical for human-computer interaction, gaming, special effects
and virtual reality. In the past, this has required extensive manual
animation. Regardless of the advances in human body and face
reconstruction, still modeling, learning and analyzing human dynamics need
further attention. In this competition we plan to push the research in this
direction, e.g. understanding human dynamics in 2D and 3D, with special
attention to garments. We provide a large-scale dataset (more than 2M
frames) of animated garments with variable topology and type. The dataset
contains paired RGB images with 3D garment vertices in a sequence. We paid
special care to garment dynamics and realistic rendering of RGB data,
including lighting, fabric type and texture. We designed three tracks so
participants can compete to develop the best method to perform 3D garment
reconstruction and texture estimation in a sequence from (1) 3D garments
and (2) RGB images.  More details are available here

Why is it important?

There has been a growing interest in the topic recently, both from a
research or industrial point of view. However, available datasets have been
limited in terms of either the number of samples or garment complexity and
topology, body shape, pose and garment dynamics (a comparison of available
datasets can be seen here <>). A
large-scale benchmark dataset has been a demand to better study the topic.
This competition provides a great opportunity to study state-of-the-art and
further push the research. Details of the dataset can be seen here

Why is it interesting to participate?


   You can test your already available method on our benchmark dataset and
   compete with other state-of-the-art methods,

   You can develop new ideas and submit your paper to NeurIPS
   Workshop/Competition Proceedings or any conference/journal of your choice,

   You can win the competition, receive a certificate and attend NeurIPS to
   present your work. We provide travel grants to the top winning teams of
   each track. Also the best student approach will be awarded by one NVIDIA

   All participants are candidates to be invited to write a joint paper
   along with the organizers. We plan to submit this paper to a top-tier

Ready to hack?

The schedule is available here
<>. You have around 4
months to finish each track.

You can enter the competition by registering at Codalab
<>. Each track is accessible by the
following links.

- Track 1, 3D to 3D garment reconstruction

- Track 2, RGB to 3D garment reconstruction

- Track 3, RGB to 3D+Texture garment reconstruction

NeurIPS competition event

In the competition track (Fri, Dec 11 - Sat, Dec 12, detailed schedule will
be released later) we will present challenge results and winning
participants can present their approaches. We also have a confirmed list of
invited speakers who are experts in the field of the competition:


   Gerard Pons-Moll, Max Planck Institute for Informatics,

   Kristen Grauman, University of Texas at Austin,

   Stefanos Zafeiriou, Imperial College London,

   Yebin Liu, Tsinghua University.


ChaLearn <>, Facebook Reality Labs
NVIDIA <>, Baidu <>

Hope to see you soon in this great event!

NeurIPS 2020 ChaLearn organizing team

Meysam Madadi, Hugo Bertiche, Wafa Bouzouita, Isabelle Guyon, Sergio

    For news of CHI books, courses & software, join CHI-RESOURCES
     mailto: [log in to unmask]

    To unsubscribe from CHI-ANNOUNCEMENTS send an email to
     mailto:[log in to unmask]

    For further details of CHI lists see