NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results

Varun Jain, Zongwei Wu, Quan Zou, Louis Florentin, Henrik Turbell, Sandeep Siddhartha, Radu Timofte, Qifan Gao, Linyan Jiang, Qing Luo, Jie Song, Yaqing Li, Summer Luo, Mae Chen, Stefan Liu, Danie Song, Huimin Zeng, Qi Chen, Ajeet Kumar Verma, Shweta Tripathi, Vinit Jakhetiya, Badri N Subhdhi, Sunil Jaiswal; Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops, 2025, pp. 1184-1194

Abstract


This paper presents a comprehensive review of the 1st Challenge on Video Quality Enhancement for Video Conferencing held at the NTIRE workshop at CVPR 2025, and highlights the problem statement, datasets, proposed solutions, and results. The aim of this challenge was to design a Video Quality Enhancement (VQE) model to enhance video quality in video conferencing scenarios by (a) improving lighting, (b) enhancing colors, (c) reducing noise, and (d) enhancing sharpness - giving a professional studio-like effect. Participants were given a differentiable Video Quality Assessment (VQA) model, training, and test videos. A total of 91 participants registered for the challenge. We received 10 valid submissions that were evaluated in a crowd-sourced framework.

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[pdf] [arXiv]
[bibtex]
@InProceedings{Jain_2025_CVPR, author = {Jain, Varun and Wu, Zongwei and Zou, Quan and Florentin, Louis and Turbell, Henrik and Siddhartha, Sandeep and Timofte, Radu and Gao, Qifan and Jiang, Linyan and Luo, Qing and Song, Jie and Li, Yaqing and Luo, Summer and Chen, Mae and Liu, Stefan and Song, Danie and Zeng, Huimin and Chen, Qi and Verma, Ajeet Kumar and Tripathi, Shweta and Jakhetiya, Vinit and Subhdhi, Badri N and Jaiswal, Sunil}, title = {NTIRE 2025 Challenge on Video Quality Enhancement for Video Conferencing: Datasets, Methods and Results}, booktitle = {Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR) Workshops}, month = {June}, year = {2025}, pages = {1184-1194} }