Scene-Generalizable Interactive Segmentation of Radiance Fields-Reference-Cited by-同舟云学术

Scene-Generalizable Interactive Segmentation of Radiance Fields

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Tang Songlin¹^ORCID,Pei Wenjie¹^ORCID,Tao Xin²^ORCID,Jia Tanghui¹^ORCID,Lu Guangming³^ORCID,Tai Yu-Wing⁴^ORCID

Affiliation:

1. Harbin Institute of Technology, Shenzhen, China

2. Kuaishou Technology, Beijing, China

3. Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies & Harbin Institute of Technology, Shenzhen, China

4. Dartmouth College, Hanover, NH, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612246

Reference51 articles.

1. Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields

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3. Emerging Properties in Self-Supervised Vision Transformers

4. Anpei Chen , Zexiang Xu , Andreas Geiger , Jingyi Yu , and Hao Su . 2022 . Tensorf: Tensorial radiance fields. In Computer Vision-ECCV 2022: 17th European Conference , Tel Aviv , Israel, October 23-27, 2022, Proceedings, Part XXXII. Springer, 333--350. Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su. 2022. Tensorf: Tensorial radiance fields. In Computer Vision-ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXXII. Springer, 333--350.

5. MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereo