BEAST3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting
Multi-view video recordings are increasingly used to capture the 3D movements of animals in experimental settings, yet extracting rich 3D representations from these recordings remains challenging. Supervised pose estimation requires extensive manual annotation, while general-purpose 3D reconstruction models trained on generic scene datasets fail on the specialized imagery and sparse-view setting of laboratory experiments. We address these limitations with BEAST3D, a self-supervised pretraining framework that learns 3D visual representations from unlabeled, calibrated multi-view video. BEAST3D uses a vision transformer to predict 3D Gaussian splats that reconstruct held-out views through d...
| Authors | Yanchen Wang, Lenny Aharon, Wangshu Zhu et al. |
|---|---|
| Primary category | q-bio.NC |
| Published | 1 June 2026 |
| Last updated at source | 1 June 2026 |
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