Summary of Neurodin: a Two-stage Framework For High-fidelity Neural Surface Reconstruction, by Yifan Wang and Di Huang and Weicai Ye and Guofeng Zhang and Wanli Ouyang and Tong He
NeuRodin: A Two-stage Framework for High-Fidelity Neural Surface Reconstruction
by Yifan Wang, Di Huang, Weicai Ye, Guofeng Zhang, Wanli Ouyang, Tong He
First submitted to arxiv on: 19 Aug 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 This paper presents a novel neural surface reconstruction framework called NeuRodin, which addresses the limitations of Signed Distance Function (SDF)-based volume rendering in capturing detailed geometric structures. By identifying and mitigating the factors that degrade surface quality in SDF-based approaches, NeuRodin achieves high-fidelity surface reconstruction while retaining the flexible optimization characteristics of density-based methods. The framework incorporates innovative strategies for transforming arbitrary topologies and reducing artifacts associated with density bias. Evaluations on the Tanks and Temples and ScanNet++ datasets demonstrate NeuRodin’s superiority, showcasing strong reconstruction capabilities in both indoor and outdoor environments using solely posed RGB captures. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary NeuRodin is a new way to create detailed 3D models from pictures. It’s better than other methods because it can handle tricky shapes and get rid of mistakes caused by the way it represents distance information. This makes NeuRodin good at reconstructing surfaces with lots of details, like buildings or trees. The researchers tested NeuRodin on real-world datasets and showed that it does a great job in both indoor and outdoor environments. |
Keywords
* Artificial intelligence * Optimization
