Abstract
Neural Radiance Fields have demonstrated impressive performance in novel view synthesis. However, NeRF and most of its variants still rely on traditional complex pipelines to provide extrinsic and intrinsic camera parameters, such as COLMAP. Recent works, like NeRFmm, BARF, and L2G-NeRF, directly treat camera parameters as learnable and estimate them through differential volume rendering. However, these methods work for forward-looking scenes with slight motions and fail to tackle the rotation scenario in practice. To overcome this limitation, we propose a novel camera parameter free neural radiance field (CF-NeRF), which incrementally reconstructs 3D representations and recovers the camera parameters inspired by incremental structure from motion. Given a sequence of images, CF-NeRF estimates camera parameters of images one by one and reconstructs the scene through initialization, implicit localization, and implicit optimization. To evaluate our method, we use a challenging real-world dataset, NeRFBuster, which provides 12 scenes under complex trajectories. Results demonstrate that CF-NeRF is robust to rotation and achieves state-of-the-art results without providing prior information and constraints.
Original language | English |
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Title of host publication | Proceedings of the 38th AAAI Conference on Artificial Intelligence |
Editors | Michael Wooldridge, Jennifer Dy, Sriraam Natarajan |
Publisher | AAAI press |
Pages | 6440-6448 |
Number of pages | 9 |
ISBN (Print) | 1577358872 , 9781577358879 |
DOIs | |
Publication status | Published - 25 Mar 2024 |
Event | 38th AAAI Conference on Artificial Intelligence, AAAI 2024 - Vancouver, Canada Duration: 20 Feb 2024 → 27 Feb 2024 https://ojs.aaai.org/index.php/AAAI/issue/archive (Conference proceeding) |
Publication series
Name | Proceedings of the AAAI Conference on Artificial Intelligence |
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Number | 6 |
Volume | 38 |
ISSN (Print) | 2159-5399 |
ISSN (Electronic) | 2374-3468 |
Conference
Conference | 38th AAAI Conference on Artificial Intelligence, AAAI 2024 |
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Country/Territory | Canada |
City | Vancouver |
Period | 20/02/24 → 27/02/24 |
Internet address |
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Scopus Subject Areas
- Artificial Intelligence
User-Defined Keywords
- 3D Computer Vision