Papers › MoSAR: Monocular Semi-Supervised Model for Avatar Reconstruction using Differentiable Shading
MoSAR: Monocular Semi-Supervised Model for Avatar Reconstruction using Differentiable Shading
Abdallah Dib, Luiz Gustavo Hafemann, Emeline Got, Trevor Anderson, Amin Fadaeinejad, Rafael M. O. Cruz, Marc-Andre Carbonneau
Reconstructing an avatar from a portrait image has many applications in multimedia, but remains a challenging research problem. Extracting reflectance maps and geometry from one image is ill-posed: recovering geometry is a one-to-many mapping problem and reflectance and light are difficult to disentangle. Accurate geometry and reflectance can be captured under the controlled conditions of a light stage, but it is costly to acquire large datasets in this fashion. Moreover, training solely with this type of data leads to poor generalization with in-the-wild images. This motivates the introduction of MoSAR, a method for 3D avatar generation from monocular images. We propose a semi-supervised training scheme that improves generalization by learning from both light stage and in-the-wild datasets. This is achieved using a novel differentiable shading formulation. We show that our approach effectively disentangles the intrinsic face parameters, producing relightable avatars. As a result, MoSAR estimates a richer set of skin reflectance maps, and generates more realistic avatars than existing state-of-the-art methods. We also introduce a new dataset, named FFHQ-UV-Intrinsics, the first public dataset providing intrinsic face attributes at scale (diffuse, specular, ambient occlusion and translucency maps) for a total of 10k subjects. The project website and the dataset are available on the following link: https://ubisoft-laforge.github.io/character/mosar/
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| 3D Face Reconstruction | REALY | MoSAR | @cheek | 1.128 (±0.303) | #5 of 24 | Archive leaderboard | report |
| 3D Face Reconstruction | REALY | MoSAR | @forehead | 1.950 (±0.559) | #5 of 24 | Archive leaderboard | report |
| 3D Face Reconstruction | REALY | MoSAR | @mouth | 1.424 (±0.462) | #5 of 24 | Archive leaderboard | report |
| 3D Face Reconstruction | REALY | MoSAR | @nose | 1.499 (±0.366) | #5 of 24 | Archive leaderboard | report |
| 3D Face Reconstruction | REALY | MoSAR | all | 1.500 | #5 of 24 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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