FactorizedHMR: Hybrid Framework for Video Human Mesh Recovery
FactorizedHMR is a two-stage framework for video human mesh recovery that addresses ambiguity in 3D body reconstruction. It uses a deterministic regression module to recover a stable torso-root anchor, then a probabilistic flow-matching module to complete non-torso articulation. The method combines composite target representation, geometry-aware supervision, and feature-aware classifier-free guidance to improve recovery of ambiguous limbs. A synthetic data pipeline supports training. The paper is published on arXiv under ID 2605.14854.
Key facts
- FactorizedHMR is a two-stage framework for video human mesh recovery.
- It uses a deterministic regression module for torso-root anchor.
- A probabilistic flow-matching module handles non-torso articulation.
- Composite target representation and geometry-aware supervision are used.
- Feature-aware classifier-free guidance preserves torso-root anchor.
- A synthetic data pipeline is introduced for training.
- The paper is on arXiv with ID 2605.14854.
- The method addresses ambiguity in 3D body reconstruction under occlusion.
Entities
Institutions
- arXiv