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Efficient 3D Reconstruction of NeRF using Camera Pose Interpolation and Photometric Bundle Adjustment

Published:23 July 2023Publication History

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References

  1. Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey. 2021. BARF: Bundle-Adjusting Neural Radiance Fields. In IEEE International Conference on Computer Vision (ICCV).Google ScholarGoogle Scholar
  2. Li Ma, Xiaoyu Li, Jing Liao, Qi Zhang, Xuan Wang, Jue Wang, and Pedro V. Sander. 2021. Deblur-NeRF: Neural Radiance Fields from Blurry Images. arXiv preprint arXiv:2111.14292 (2021).Google ScholarGoogle Scholar
  3. Ben Mildenhall, Pratul P. Srinivasan, Matthew Tancik, Jonathan T. Barron, Ravi Ramamoorthi, and Ren Ng. 2020. NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. In European Conference on Computer Vision (ECCV).Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Johannes L. Schonberger and Jan-Michael Frahm. 2016. Structure-From-Motion Revisited. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).Google ScholarGoogle Scholar
  5. Matthew Tancik, Ethan Weber, Evonne Ng, Ruilong Li, Brent Yi, Justin Kerr, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, David McAllister, and Angjoo Kanazawa. 2023. Nerfstudio: A Modular Framework for Neural Radiance Field Development. arXiv preprint arXiv:2302.04264 (2023).Google ScholarGoogle Scholar

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  1. Efficient 3D Reconstruction of NeRF using Camera Pose Interpolation and Photometric Bundle Adjustment

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    • Published in

      cover image ACM Conferences
      SIGGRAPH '23: ACM SIGGRAPH 2023 Posters
      July 2023
      111 pages
      ISBN:9798400701528
      DOI:10.1145/3588028

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      Publication History

      • Published: 23 July 2023

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