NTIRE 2024 Challenge on HR Depth from Images of Specular and Transparent Surfaces
Pierluigi Zama Ramirez, Fabio Tosi, Luigi Di Stefano, Radu Timofte, Alex Costanzino, Matteo Poggi, Samuele Salti, Stefano Mattoccia, Yangyang Zhang, Cailin Wu, Zhuangda He, Shuangshuang Yin, Jiaxu Dong, Yangchenxu Liu, Hao Jiang, Jun Shi, A Yong, Yixiang Jin, Dingzhe Li, Bingxin Ke, Anton Obukhov, Tianfu Wang, Nando Metzger, Shengyu Huang, Konrad Schindler, Yachuan Huang, Jiaqi Li, Junrui Zhang, Yiran Wang, Zihao Huang, Tianqi Liu, Zhiguo Cao, Pengzhi Li, Jui-Lin Wang, Wenjie Zhu, Hui Geng, Yuxin Zhang, Long Lan, Kele Xu, Tao Sun, Qisheng Xu, Sourav Saini, Aashray Gupta, Sahaj K. Mistry, Aryan Shukla, Vinit Jakhetiya, Sunil Jaiswal, Yuejin Sun, Zhuofan Zheng, Yi Ning, Jen-Hao Cheng, Hou-I Liu, Hsiang-Wei Huang, Cheng-Yen Yang, Zhongyu Jiang, Yi-Hao Peng, Aishi Huang, Jenq–Neng Hwang
Abstract
This paper reports on the NTIRE 2024 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 2024. 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 120 registered participants. In the final testing stage, 2 and 8 participating teams submitted their models and fact sheets for the two tracks.