NTIRE 2023 Quality Assessment of Video Enhancement Challenge

Xiaohong Liu, Xiongkuo Min, Wei Sun, Yulun Zhang , Kai Zhang, Radu Timofte, Guangtao Zhai, Yixuan Gao, Yuqin Cao, Tengchuan Kou, Yunlong Dong, Ziheng Jia , Yilin Li, Kai Zhao, Heng Cong, Hang Shi, Zhiliang Ma, Mirko Agarla, Zhiwei Huang, Hongye Liu, Ironhead Chuang, Haotian Fan, Shiqi Zhou, Yu Lai, Wenqi Wang, Haoning Wu, Chunzheng Zhu, Shiling Zhao, Hanene Brachemi Meftah, Tengfei Shi, Azadeh Mansouri; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, pp. 1551-1569

Abstract

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement Workshop (NTIRE) at CVPR 2023. This challenge is to address a major challenge in the field of video processing, namely, video quality assessment (VQA) for enhanced videos. The challenge uses the VQA Dataset for Perceptual Video Enhancement (VDPVE), which has a total of 1211 enhanced videos, including 600 videos with color, brightness, and contrast enhancements, 310 videos with deblurring, and 301 deshaked videos. The challenge has a total of 167 registered participants. 61 participating teams submitted their prediction results during the development phase, with a total of 3168 submissions. A total of 176 submissions were submitted by 37 participating teams during the final testing phase. Finally, 19 participating teams submitted their models and fact sheets, and detailed the methods they used. Some methods have achieved better results than baseline methods, and the winning methods have demonstrated superior prediction performance.

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[bibtex]
@InProceedings{Liu_2023_CVPR, author = {Liu, Xiaohong and Min, Xiongkuo and Sun, Wei and Zhang, Yulun and Zhang, Kai and Timofte, Radu and Zhai, Guangtao and Gao, Yixuan and Cao, Yuqin and Kou, Tengchuan and Dong, Yunlong and Jia, Ziheng and Li, Yilin and Zhao, Kai and Cong, Heng and Shi, Hang and Ma, Zhiliang and Agarla, Mirko and Huang, Zhiwei and Liu, Hongye and Chuang, Ironhead and Fan, Haotian and Zhou, Shiqi and Lai, Yu and Wang, Wenqi and Wu, Haoning and Zhu, Chunzheng and Zhao, Shiling and Meftah, Hanene Brachemi and Shi, Tengfei and Mansouri, Azadeh}, title = {NTIRE 2023 Quality Assessment of Video Enhancement Challenge}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2023}, pages = {1551-1569} }