3D face reconstruction from multiple 2D images


Reconstructing 3D facial shapes from 2D images is critical to face analysis applications. However, it is difficult to get 3D ground truth shapes for face images because of the requirements for special sensors and constrained environment in data acquisition. In order to overcome the scarcity of 3D face datasets, a real-world, large-scale, high-precision multi-modal dataset, namely PixelAI-3DFace, is released for bridge the gap between 2D images and 3D shapes in this challenge.
Input: left, frontal and right side 2D facial images captured by self-customized trinocular high resolution camera.
Output: 106 3D facial landmarks.


1st prize: USD$ 9,000
2nd prize: USD$ 4,000
3rd prize: USD$ 2,000

Important Date

Time zone: Beijing, UTC+8

April 1th, 10:00:00, 2021
May 6st, 10:00:00, 2021
June 4th, 10:00:00, 2021
June 8th, 10:00:00, 2021
June 20th, 2021
Training / validation set released
Testing set released and submission opened
Submission deadline
Challenge winners notified
Winners present at CVPR 2021 Workshop

Task Rules

  1. Please refer to the link


Data Statistics

Set Subjects Images 3D Scans 3D Meshes
Training Set 523 15,612 5,204 5,204
Validation Set 106 2,691 897 897
Testing Set 225 7,128 2,376 2,376