5 papers
Generative Video Compression Based on Hierarchical Referencing
Daowen Li, Ding Ding, Zifu Zhang +2
Diffusion-based generative video compression has emerged as a promising paradigm to improve perceptual quality, where latent frames are required to be encoded efficiently while ser…
Controllable Generative Video Compression
Ding Ding, Daowen Li, Ying Chen +4
Perceptual video compression adopts generative video modeling to improve perceptual realism but frequently sacrifices signal fidelity, diverging from the goal of video compression…
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…
ProGVC: Progressive-based Generative Video Compression via Auto-Regressive Context Modeling
Daowen Li, Ruixiao Dong, Ying Chen +3
Perceptual video compression leverages generative priors to reconstruct realistic textures and motions at low bitrates. However, existing perceptual codecs often lack native suppor…
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…