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20222026
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cs.CV2026

NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results

Xin Li, Jiachao Gong, Xijun Wang +75

This paper presents an overview of the NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models. This challenge utilizes a new short-form UGC (S-…

cs.CV2025

Rethinking Diffusion Model-Based Video Super-Resolution: Leveraging Dense Guidance from Aligned Features

Jingyi Xu, Meisong Zheng, Ying Chen +3

Diffusion model (DM) based Video Super-Resolution (VSR) approaches achieve impressive perceptual quality. However, they suffer from error accumulation, spatial artifacts, and a tra…

cs.CV2025

NTIRE 2025 Challenge on UGC Video Enhancement: Methods and Results

Nikolay Safonov, Alexey Bryncev, Andrey Moskalenko +28

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…

cs.CV2024

Enhancing Quality of Compressed Images by Mitigating Enhancement Bias Towards Compression Domain

Qunliang Xing, Mai Xu, Shengxi Li +4

Existing quality enhancement methods for compressed images focus on aligning the enhancement domain with the raw domain to yield realistic images. However, these methods exhibit a…

cs.CV2022

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Meisong Zheng +75

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…

cs.CV2022

Progressive Training of A Two-Stage Framework for Video Restoration

Meisong Zheng, Qunliang Xing, Minglang Qiao +4

As a widely studied task, video restoration aims to enhance the quality of the videos with multiple potential degradations, such as noises, blurs and compression artifacts. Among v…