Research map / Detection and segmentation / Open-set and few-shot detection
Unsupervised Learning of Compositional Scene Representations from Multiple Unspecified Viewpoints
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Maintain shared object attributes across viewpoints rather than use separate attributes per viewpoint | OCLOC · CLEVR-M1 | ARI-O: 0.269$\pm$1e-2 -> 0.948$\pm$3e-3 | Helped |
| Maintain shared object attributes across viewpoints rather than use separate attributes per viewpoint | OCLOC · CLEVR-M2 | ARI-O: 0.274$\pm$1e-2 -> 0.941$\pm$3e-3 | Helped |
| Maintain shared object attributes across viewpoints rather than use separate attributes per viewpoint | OCLOC · CLEVR-M3 | ARI-O: 0.278$\pm$1e-2 -> 0.939$\pm$5e-3 | Helped |
| Maintain shared object attributes across viewpoints rather than use separate attributes per viewpoint | OCLOC · CLEVR-M4 | ARI-O: 0.280$\pm$6e-3 -> 0.923$\pm$4e-3 | Helped |
| Learn viewpoint representations without viewpoint annotations | OCLOC compared with MulMON · CLEVR-M1 | ARI-O: 0.927$\pm$5e-3 -> 0.948$\pm$3e-3 | Helped |
| Learn viewpoint representations without viewpoint annotations | OCLOC compared with MulMON · CLEVR-M2 | ARI-O: 0.939$\pm$3e-3 -> 0.941$\pm$3e-3 | No clear effect |
| Learn viewpoint representations without viewpoint annotations | OCLOC compared with MulMON · CLEVR-M3 | ARI-O: 0.938$\pm$2e-3 -> 0.939$\pm$5e-3 | No clear effect |
| Learn viewpoint representations without viewpoint annotations | OCLOC compared with MulMON · CLEVR-M4 | ARI-O: 0.936$\pm$3e-3 -> 0.923$\pm$4e-3 | Hurt |
| Use a curriculum, pretraining on CLEVR-M1/CLEVR-M2 before training on CLEVR-M3/CLEVR-M4 | OCLOC · CLEVR-M3/CLEVR-M4 | unspecified | Helped |
Closest papers by meaning
- Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation (ICML 2019 · similarity 0.91)
- Compositional Scene Understanding through Inverse Generative Modeling (ICML 2025 · similarity 0.90)
- Novel View Synthesis with Pixel-Space Diffusion Models (CVPR 2025 · similarity 0.87)
- Unlocking Compositional Generalization in Continual Few-Shot Learning (NeurIPS 2026 · similarity 0.86)
- Not Only Text: Exploring Compositionality of Visual Representations in Vision-Language Models (CVPR 2025 · similarity 0.86)
- SCION: Scene Composition via Instanced Neural Primitives (NeurIPS 2026 · similarity 0.86)
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