Chen, Jiahao, Qin, Yipeng  ORCID: https://orcid.org/0000-0002-1551-9126, Liu, Lingjie, Lu, Jiangbo and Li, Guanbin
2024.
NeRF-HuGS: Improved neural radiance fields in non-static scenes using heuristics-guided segmentation.
Presented at: The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024,
Seattle, WA, USA,
17-21 June 2024.
Proceedings of the Conference on Computer Vision and Pattern Recognition.
IEEE,
pp. 19436-19446.
10.1109/CVPR52733.2024.01838
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Abstract
Neural Radiance Field (NeRF) has been widely recognized for its excellence in novel view synthesis and 3D scene reconstruction. However, their effectiveness is in-herently tied to the assumption of static scenes, rendering them susceptible to undesirable artifacts when confronted with transient distractors such as moving objects or shad-ows. In this work, we propose a novel paradigm, namely “Heuristics-Guided Segmentation” (HuGS), which signifi-cantly enhances the separation of static scenes from tran-sient distractors by harmoniously combining the strengths of hand-crafted heuristics and state-of-the-art segmentation models, thus significantly transcending the limitations of previous solutions. Furthermore, we delve into the metic-ulous design of heuristics, introducing a seamless fusion of Structure-from-Motion (SfM)-based heuristics and color residual heuristics, catering to a diverse range of texture profiles. Extensive experiments demonstrate the superiority and robustness of our method in mitigating transient dis-tractors for NeRFs trained in non-static scenes. Project page: https://cnhaox.github.io/NeRF-HuGS/
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | IEEE |
| ISBN: | 979-8-3503-5301-3 |
| ISSN: | 1063-6919 |
| Date of First Compliant Deposit: | 9 April 2024 |
| Date of Acceptance: | 27 February 2024 |
| Last Modified: | 08 Apr 2025 14:01 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/167524 |
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