mlsanityData to 14 Oct 2026

NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results

arXiv 2505.03007 ↗First posted 5 May 2025cs.CVcited by 12

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 39 of its 72 references that are in the map. First posted on arXiv 5 May 2025.

Builds on

39 of 72 references.

References · 39

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  2. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  3. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,887
  4. 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 970
  5. 2022Simple Baselines for Image Restorationcited by 708
  6. 2016Optical Flow Estimation using a Spatial Pyramid Networkcited by 424
  7. 2017DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networkscited by 367
  8. 2021BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignmentcited by 342
  9. 2024One-Step Effective Diffusion Network for Real-World Image Super-Resolutioncited by 246
  10. 2020Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-timecited by 163
  11. 2020Learning for Video Compression with Hierarchical Quality and Recurrent Enhancementcited by 90
  12. 2021Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancementcited by 60
27 more
  1. 2024The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Reportcited by 57
  2. 2020Video Super Resolution Based on Deep Learning: A Comprehensive Surveycited by 54
  3. 2019MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Videocited by 50
  4. 2021NTIRE 2021 Challenge on Image Deblurringcited by 50
  5. 2020Space-Time-Aware Multi-Resolution Video Enhancementcited by 49
  6. 2024NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Resultscited by 40
  7. 2024NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Resultscited by 29
  8. 2017Enhancing Quality for HEVC Compressed Videoscited by 28
  9. 2020Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Videocited by 26
  10. 2021NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Resultscited by 26
  11. 2025The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Reportcited by 26
  12. 2025NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Resultscited by 25
  13. 2023VDPVE: VQA Dataset for Perceptual Video Enhancementcited by 22
  14. 2025NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Resultscited by 22
  15. 2025The Tenth NTIRE 2025 Image Denoising Challenge Reportcited by 21
  16. 2022NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Resultscited by 20
  17. 2022AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Resultscited by 20
  18. 2024Motion-adaptive Separable Collaborative Filters for Blind Motion Deblurringcited by 20
  19. 2019Non-Local ConvLSTM for Video Compression Artifact Reductioncited by 19
  20. 2025NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Resultscited by 16
  21. 2020End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensationcited by 14
  22. 2025NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Resultscited by 14
  23. 2025NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Resultscited by 12
  24. 2019Quality-Gated Convolutional LSTM for Enhancing Compressed Videocited by 11
  25. 2025NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Studycited by 11
  26. 2025NTIRE 2025 Challenge on Real-World Face Restoration: Methods and Resultscited by 10
  27. 2021NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Dataset and Studycited by 9

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 10; 2026: 2.

12 papers.