10 papers
ZeroGVC: Zero-Shot Generative Video Compression with Autoregressive Diffusion Priors
Yixin Gao, Xiaohan Pan, Lin Liu +3
Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existing approaches require addition…
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…
LoVoRA: Text-guided and Mask-free Video Object Removal and Addition with Learnable Object-aware Localization
Zhihan Xiao, Lin Liu, Yixin Gao +4
Text-guided video editing, particularly for object removal and addition, remains a challenging task due to the need for precise spatial and temporal consistency. Existing methods o…
Diff-ICMH: Harmonizing Machine and Human Vision in Image Compression with Generative Prior
Ruoyu Feng, Yunpeng Qi, Jinming Liu +4
Image compression methods are usually optimized isolatedly for human perception or machine analysis tasks. We reveal fundamental commonalities between these objectives: preserving…
OmniQuality-R: Advancing Reward Models Through All-Encompassing Quality Assessment
Yiting Lu, Fengbin Guan, Yixin Gao +8
Current visual evaluation approaches are typically constrained to a single task. To address this, we propose OmniQuality-R, a unified reward modeling framework that transforms mult…
Comp-X: On Defining an Interactive Learned Image Compression Paradigm With Expert-driven LLM Agent
Yixin Gao, Xin Li, Xiaohan Pan +7
We present Comp-X, the first intelligently interactive image compression paradigm empowered by the impressive reasoning capability of large language model (LLM) agent. Notably, com…