4D-HOF: Hand-Object Flow Matching for Feed-Forward 4D Interaction Reconstruction
[Widzenie komputerowe] Autorzy: Shiqi Li, Sean Cho, Yijie Li i 3 więcej
Existing methods for 4D hand-object reconstruction often rely on costly per-sequence optimization, while generative approaches typically synthesize interactions from random noise, which can lead to unstable interaction prediction. We introduce 4D-HOF, a feed-forward framework that reconstructs 4D hand-object interactions from coarse but informative estimates produced by vision foundation models. Concretely, we learn a conditional flow matching model that transports foundation-model-derived hand-object states toward an interaction manifold, allowing the model to correct errors in translation, rotation, and alignment in a feed-forward manner. A key advantage of our generative formulation is that it naturally enables test-time guidance within the transport process. Rather than applying a separate post-hoc optimization after reconstruction, we directly steer the evolving generative states u…
- Kategoria arxiv
- cs.CV
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- Widzenie komputerowe