NTIRE 2023 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, Jun Shi, Dafeng Zhang, Yong A, Yixiang Jin, Dingzhe Li, Chao Li, Zhiwen Liu, Qi Zhang, Yixing Wang, Shi Yin; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, pp. 1384-1395

Abstract

This paper reports about the NTIRE 2023 challenge on HR Depth From images of Specular and Transparent surfaces, held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2023. This challenge is held to boost the research on depth estimation, mainly to deal with two of the open issues in the field: high-resolution images and non-Lambertian surfaces characterizing specular and transparent materials. The challenge is divided into two tracks: a stereo track focusing on disparity estimation from rectified pairs and a mono track dealing with single-image depth estimation. The challenge attracted about 100 registered participants for the two tracks. In the final testing stage, 5 participating teams submitted their models and fact sheets, 2 and 3 for the Stereo and Mono tracks, respectively.

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[bibtex]
@InProceedings{Ramirez_2023_CVPR, author = {Ramirez, Pierluigi Zama and Tosi, Fabio and Di Stefano, Luigi and Timofte, Radu and Costanzino, Alex and Poggi, Matteo and Salti, Samuele and Mattoccia, Stefano and Shi, Jun and Zhang, Dafeng and A, Yong and Jin, Yixiang and Li, Dingzhe and Li, Chao and Liu, Zhiwen and Zhang, Qi and Wang, Yixing and Yin, Shi}, title = {NTIRE 2023 Challenge on HR Depth From Images of Specular and Transparent Surfaces}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {1384-1395} }