NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results
This addresses the practical need for better video quality on short-form platforms, but it is incremental as it builds on existing enhancement methods through a competition framework.
The paper tackled the problem of enhancing user-generated content videos with real-world degradations by organizing a challenge that attracted over 25 teams, with 7 finalists improving visual quality based on subjective assessments from over 8000 voters.
This paper presents an overview of the NTIRE 2025 Challenge on UGC Video Enhancement. The challenge constructed a set of 150 user-generated content videos without reference ground truth, which suffer from real-world degradations such as noise, blur, faded colors, compression artifacts, etc. The goal of the participants was to develop an algorithm capable of improving the visual quality of such videos. Given the widespread use of UGC on short-form video platforms, this task holds substantial practical importance. The evaluation was based on subjective quality assessment in crowdsourcing, obtaining votes from over 8000 assessors. The challenge attracted more than 25 teams submitting solutions, 7 of which passed the final phase with source code verification. The outcomes may provide insights into the state-of-the-art in UGC video enhancement and highlight emerging trends and effective strategies in this evolving research area. All data, including the processed videos and subjective comparison votes and scores, is made publicly available at https://github.com/msu-video-group/NTIRE25_UGC_Video_Enhancement.