Summary of Reconx: Reconstruct Any Scene From Sparse Views with Video Diffusion Model, by Fangfu Liu et al.
ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
by Fangfu Liu, Wenqiang Sun, Hanyang Wang, Yikai Wang, Haowen Sun, Junliang Ye, Jun Zhang, Yueqi Duan
First submitted to arxiv on: 29 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Graphics (cs.GR)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed paper, ReconX, presents a novel approach to 3D scene reconstruction from sparse-view scenarios, which are often plagued by artifacts and distortions. By reframing the problem as a temporal generation task, the authors leverage pre-trained video diffusion models to generate detailed scenes that preserve 3D consistency. The method first constructs a global point cloud and encodes it into a contextual space as the 3D structure condition, then synthesizes video frames guided by this condition. Finally, the 3D scene is recovered through confidence-aware 3D Gaussian Splatting optimization. ReconX outperforms state-of-the-art methods in terms of quality and generalizability on various real-world datasets. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary ReconX is a new way to create detailed 3D scenes from few photos. Currently, this task is tricky because there aren’t enough views to get an accurate result. The authors found that by using big video models as a starting point, they could generate more realistic and consistent scenes. Their approach involves creating a map of the scene’s points in space and then using this map to guide the generation of video frames. This process ensures that the resulting 3D scene looks good from all angles. ReconX is better than other methods at recreating real-world scenes. |
Keywords
» Artificial intelligence » Diffusion » Optimization
