FAMOS: Feed-Forward 3D Articulation Modeling from Sparse Observations
[Widzenie komputerowe] Autorzy: Kevin Qu, Tao Sun, Massimiliano Viola i 5 więcej
Modeling articulated objects from sparse monocular views is challenging because each observation reveals only partial geometry and motion evidence. Most feed-forward methods infer articulation from a single observation and therefore rely heavily on learned category-level shape priors. We present FAMOS, a feed-forward model that predicts movable-part segmentation and joint parameters from a sparse, unordered set of partial point clouds. Our model jointly reasons over multiple observations and naturally supports a variable number of inputs, including a single view. To aggregate articulation cues across observations, we introduce a Multi-state Articulation Transformer with alternating state-wise and global attention. We further propose an observed articulation span objective that supervises the motion range each part exhibits across the input observations, encouraging the model to leverage…
- Kategoria arxiv
- cs.CV
- Kategoria
- Widzenie komputerowe