NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results

Longguang Wang, Yulan Guo, Juncheng Li, Hongda Liu, Yang Zhao, Yingqian Wang, Zhi Jin, Shuhang Gu, Radu Timofte, and challenge participants including Jian Wang, Yuqi Miao, Baiang Li, Kejie Zhao, and others.

IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2024.

arXiv PDF CVF Open Access Challenge code Jian Wang homepage

Abstract

This paper summarizes the 3rd NTIRE challenge on stereo image super-resolution with a focus on new solutions and results. The challenge aims to super-resolve low-resolution stereo image pairs to high-resolution outputs under a limited computational budget, establishing a benchmark for efficient stereo image super-resolution.

Author Note

The arXiv and CVF landing metadata list the organizer authors, while the paper PDF includes challenge teams and participants in the method and team sections. This page provides a standard scholarly entry for indexing and citation lookup.

BibTeX

@inproceedings{wang2024ntirestereosr,
  title={NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results},
  author={Wang, Longguang and Guo, Yulan and Li, Juncheng and Liu, Hongda and Zhao, Yang and Wang, Yingqian and Jin, Zhi and Gu, Shuhang and Timofte, Radu and Cong, Runmin and Yang, Yuqiang and Zhang, Zhiming and Yang, Jingjing and Bao, Long and Sun, Heng and Yuan, Weijun and Li, Zhan and Kuang, Wenqin and Guan, Ruijin and Wang, Jian and Miao, Yuqi and Li, Baiang and Zhao, Kejie and others},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  pages={6198--6207},
  doi={10.48550/arXiv.2409.16947},
  eprint={2409.16947},
  archivePrefix={arXiv},
  year={2024}
}