Research map / 3D vision / NeRF and radiance fields
Neural Scene Graphs for Dynamic Scenes
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI reconstruction | PSNR: 24.18 -> 26.66 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI reconstruction | SSIM: 0.677 -> 0.806 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI reconstruction | LPIPS: 0.425 -> 0.186 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI reconstruction | tOF × 10⁶: 1.443 -> 0.765 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI reconstruction | tLP × 100: 0.897 -> 0.246 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI novel composition | PSNR: 19.68 -> 25.11 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI novel composition | SSIM: 0.593 -> 0.789 | Helped |
| represent dynamic scenes as scene graphs with separate object and background representations | Neural Scene Graphs · KITTI novel composition | LPIPS: 0.473 -> 0.204 | Helped |
Closest papers by meaning
- Multi-Level Neural Scene Graphs for Dynamic Urban Environments (CVPR 2024 · similarity 0.91)
- Neural Atlas Graphs for Dynamic Scene Decomposition and Editing (NeurIPS 2025 · similarity 0.89)
- DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$ (ICLR 2024 · similarity 0.88)
- OSN: Infinite Representations of Dynamic 3D Scenes from Monocular Videos (ICML 2024 · similarity 0.88)
- DyST: Towards Dynamic Neural Scene Representations on Real-World Videos (ICLR 2024 · similarity 0.88)
- EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision (ICLR 2024 · similarity 0.87)
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