BEA-GS: BEyond RAdiance Supervision in 3DGS for Precise Object Extraction
Most Gaussian Splatting techniques that provide a 3D semantic representation of the scene do not optimize the underlying 3D geometry, making object-level editing or asset extraction challenging. Recent methods, such as COBGS, Trace3D, ObjectGS, acknowledge this limitation and propose approaches that modify the scene's geometry to represent the underlying semantics. We advance this concept further by proposing a novel solution that provides near perfect boundaries in object extraction. We do so by introducing two new losses in the optimization that take care of: 1) a loss that modifies the geometry of visible Gaussians to respect semantic boundaries, and 2) a loss that adjusts the geometry...
| Authors | Alessio Mazzucchelli, Maria Naranjo-Almeida, Jorge Bustos-Sanchez et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 May 2026 |
| Last updated at source | 10 May 2026 |
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