Meta Research

We present a system that animates children’s drawings of the human figure, is robust to the variance inherent in these depictions, and is simple enough for anyone to use.

Focus on the underexplored question of how to personalize these systems while preserving privacy.

We introduce a simple framework that operates on 3D points of single objects or whole scenes coupled with category-agnostic largescale training from diverse RGB-D videos.

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Presenting InterWild, bringing MoCap and ITW samples to shared domains for robust 3D interacting hands recovery in the wild with limited ITW 2D/3D interacting hands data.

We present the first neural relighting approach for rendering high fidelity personalized hands that can be animated in real-time under novel illumination.

In this work, we propose a 3D compositional morphable model of eyeglasses that accurately incorporates high-fidelity geometric and photometric interaction effects.

Propose to rethink visual affordances as a means to bridge vision and robotics. We argue that rich video datasets of humans interacting can offer a lot more actionable ....

We consider the problem of reconstructing a dynamic scene observed from a stereo camera.

To address these issues, we propose a novel framework Feature Representation Learning with adaptive Displacement Generation and Transformer fusion (FRL-DGT), in which a...