FactorizedHMR: A Hybrid Framework for Video Human Mesh Recovery
Human Mesh Recovery (HMR) is fundamentally ambiguous: under occlusion or weak depth cues, multiple 3D bodies can explain the same image evidence. This ambiguity is not uniform across the body, as torso pose and root structure are often relatively well constrained, whereas distal articulations such as the arms and legs are more uncertain. Building on this observation, we propose FactorizedHMR, a two-stage framework that treats these two regimes differently. A deterministic regression module first recovers a stable torso-root anchor, and a probabilistic flow-matching module then completes the remaining non-torso articulation. To make this completion reliable, we combine a composite target r...
| Authors | Patrick Kwon, Chen Chen |
|---|---|
| Primary category | cs.CV |
| Published | 14 May 2026 |
| Last updated at source | 8 October 2026 |
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