ShapeSplat: A Large-scale Dataset of Gaussian Splats and Their Self-Supervised Pretraining

Understand

3D Gaussian Splatting (3DGS) has become the de facto method of 3D representation in many vision tasks.

• This calls for the 3D understanding directly in this representation space.
• To facilitate the research in this direction, we first build ShapeSplat, a large-scale dataset of 3DGS using the commonly used ShapeNet, ModelNet and Objaverse datasets.
• Our dataset ShapeSplat consists of 206K objects spanning over 87 unique categories, whose labels are in accordance with the respective datasets.