Research map / 3D vision / 3D generation
SceneScape: Text-Driven Consistent Scene Generation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add test-time depth finetuning (ablation) | SceneScape · 20 videos, 10 prompts | depth SI-RMSE | Helped |
| add test-time decoder finetuning (ablation) | SceneScape · 20 videos, 10 prompts | COLMAP reprojection error | Helped |
| use unified mesh instead of 2D depth-aware splatting (ablation) | SceneScape · 20 videos, 10 prompts | COLMAP metrics (pose, reprojection, SI-RMSE, completeness) | Helped |
| use unified mesh instead of 2D splatting (ablation) | SceneScape · AMT user study | user preference | Helped |
| add depth finetuning (ablation) | SceneScape · AMT user study | user preference | No clear effect |
| use SceneScape instead of VideoFusion | text-driven video generation · AMT visual quality | % preference: 95.97 | Helped |
| use SceneScape instead of GEN-1 | text-driven video generation · AMT visual quality | % preference: 69.34 | Helped |
| use SceneScape instead of GEN-1 | text-driven video generation · CLIP text similarity | CLIP text-similarity | No clear effect |
Closest papers by meaning
- 3D-SceneDreamer: Text-Driven 3D-Consistent Scene Generation (CVPR 2024 · similarity 0.90)
- 4Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models (NeurIPS 2024 · similarity 0.88)
- Generative Photography: Scene-Consistent Camera Control for Realistic Text-to-Image Synthesis (CVPR 2025 · similarity 0.88)
- ViewDiff: 3D-Consistent Image Generation with Text-to-Image Models (CVPR 2024 · similarity 0.88)
- WonderJourney: Going from Anywhere to Everywhere (CVPR 2024 · similarity 0.87)
- StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation (NeurIPS 2024 · similarity 0.87)
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