NVIDIA Axolotl3D uses images, masks and point clouds to complete 3D shapes
jonLorraine9 · x · 2026-07-29
NVIDIA’s Spatial Intelligence Lab presents Axolotl3D, a unified framework for faithful 3D shape completion and editing from partial observations.
- The model jointly conditions on images, visibility masks, camera parameters, and partial point clouds.
- The point cloud acts as a geometric anchor, while camera parameters keep multi-view alignment consistent.
- A unified training strategy synthesizes diverse conditioning regimes from large-scale 3D data.
- Experiments on Toys4K and OmniObject3D show state-of-the-art results in clean and occluded settings, plus strong performance in real-world reconstruction and geometry-consistent editing.
Related event: NVIDIA Introduces Axolotl3D for Unified 3D Completion(2 posts)→
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