TriSplat: Simulation-Ready Feed-Forward 3D Scene Reconstruction
- Published
- Source
- arXiv
- Paper number
- 231
- Field
- Computer Vision
- arXiv ID
- 2605.26115
Key points
- It proposes a structure that uses oriented triangles instead of Gaussians as the primitive, so the rendered output is already a mesh.
- It derives normals from the predicted point map and refines them with an image-conditioned U-Net to keep triangle orientation aligned with geometry.
- Mono-normal bootstrapping plus validity-aware masking stabilizes early training, and opacity and blur scheduling gradually sharpen the surface.
- It achieves better geometry fidelity and competitive novel-view synthesis quality than Gaussian feed-forward baselines on RealEstate10K and DL3DV.
- Zero-shot ScanNet evaluation confirms cross-dataset generalization.
- It can be used directly in physics engines, collision detectors, and standard rendering pipelines without post-processing such as TSDF fusion.
Paper links
External research summaries. These are not HDATF publications or measured product results.