Research map / 3D vision / Face and shape
Learning Shape Abstractions by Assembling Volumetric Primitives
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Learn existence probabilities and use a parsimony reward to reduce the number of primitives | Volumetric Primitives · ShapeNet chairs, airplanes, and animals | reconstruction loss | Hurt |
| Learn existence probabilities and use a parsimony reward to reduce the number of primitives | Volumetric Primitives · ShapeNet chairs, airplanes, and animals | number of primitives used | Helped |
| Train the volume-based model first with fixed high existence probabilities, then learn primitive existence | Volumetric Primitives · ShapeNet chairs, airplanes, and animals | primitive alignment | Helped |
Closest papers by meaning
- Neural Parts: Learning Expressive 3D Shape Abstractions With Invertible Neural Networks (CVPR 2021 · similarity 0.88)
- ShapeClipper: Scalable 3D Shape Learning From Single-View Images via Geometric and CLIP-Based Consistency (CVPR 2023 · similarity 0.88)
- StructEdit: Learning Structural Shape Variations (CVPR 2020 · similarity 0.88)
- Learning to Infer and Execute 3D Shape Programs (ICLR 2019 · similarity 0.88)
- Learning elementary structures for 3D shape generation and matching (NeurIPS 2019 · similarity 0.88)
- Learning Partonomic 3D Reconstruction from Image Collections (CVPR 2025 · similarity 0.86)
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