NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866913881289392128 |
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| author | Ramirez, Pierluigi Zama Tosi, Fabio Di Stefano, Luigi Timofte, Radu Costanzino, Alex Poggi, Matteo Salti, Samuele Mattoccia, Stefano Zhang, Zhe Yang, Yang Chen, Wu Ming, Anlong Zhao, Mingshuai Yu, Mengying Gao, Shida Wang, Xiangfeng Xue, Feng Shi, Jun Yang, Yong A, Yong Jin, Yixiang Li, Dingzhe Shukla, Aryan Frija-Altarac, Liam Toews, Matthew Geng, Hui Wan, Tianjiao Gao, Zijian Xu, Qisheng Xu, Kele Zang, Zijian Pinjari, Jameer Babu Purohit, Kuldeep Lavreniuk, Mykola Cao, Jing Li, Shenyi Jiang, Kui Jiang, Junjun Huang, Yong |
| author_facet | Ramirez, Pierluigi Zama Tosi, Fabio Di Stefano, Luigi Timofte, Radu Costanzino, Alex Poggi, Matteo Salti, Samuele Mattoccia, Stefano Zhang, Zhe Yang, Yang Chen, Wu Ming, Anlong Zhao, Mingshuai Yu, Mengying Gao, Shida Wang, Xiangfeng Xue, Feng Shi, Jun Yang, Yong A, Yong Jin, Yixiang Li, Dingzhe Shukla, Aryan Frija-Altarac, Liam Toews, Matthew Geng, Hui Wan, Tianjiao Gao, Zijian Xu, Qisheng Xu, Kele Zang, Zijian Pinjari, Jameer Babu Purohit, Kuldeep Lavreniuk, Mykola Cao, Jing Li, Shenyi Jiang, Kui Jiang, Junjun Huang, Yong |
| contents | This paper reports on the NTIRE 2025 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhancement (NTIRE) workshop at CVPR 2025. This challenge aims to advance the research on depth estimation, specifically to address two of the main open issues in the field: high-resolution and non-Lambertian surfaces. The challenge proposes two tracks on stereo and single-image depth estimation, attracting about 177 registered participants. In the final testing stage, 4 and 4 participating teams submitted their models and fact sheets for the two tracks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_05815 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces Ramirez, Pierluigi Zama Tosi, Fabio Di Stefano, Luigi Timofte, Radu Costanzino, Alex Poggi, Matteo Salti, Samuele Mattoccia, Stefano Zhang, Zhe Yang, Yang Chen, Wu Ming, Anlong Zhao, Mingshuai Yu, Mengying Gao, Shida Wang, Xiangfeng Xue, Feng Shi, Jun Yang, Yong A, Yong Jin, Yixiang Li, Dingzhe Shukla, Aryan Frija-Altarac, Liam Toews, Matthew Geng, Hui Wan, Tianjiao Gao, Zijian Xu, Qisheng Xu, Kele Zang, Zijian Pinjari, Jameer Babu Purohit, Kuldeep Lavreniuk, Mykola Cao, Jing Li, Shenyi Jiang, Kui Jiang, Junjun Huang, Yong Computer Vision and Pattern Recognition This paper reports on the NTIRE 2025 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhancement (NTIRE) workshop at CVPR 2025. This challenge aims to advance the research on depth estimation, specifically to address two of the main open issues in the field: high-resolution and non-Lambertian surfaces. The challenge proposes two tracks on stereo and single-image depth estimation, attracting about 177 registered participants. In the final testing stage, 4 and 4 participating teams submitted their models and fact sheets for the two tracks. |
| title | NTIRE 2025 Challenge on HR Depth from Images of Specular and Transparent Surfaces |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.05815 |