1 citations · 1 across the 10 of their papers we have counts for
8 papers · 1 filter
Dense-Prior-Guided Generative Video Compression
Ding Ding, Daowen Li, Ying Chen +4
Diffusion-based generative video compression offers a promising paradigm for low-bitrate reconstruction, but existing keyframe-based controllable approaches rely on sparse priors f…
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…
Why Compress What You Can Generate? When GPT-4o Generation Ushers in Image Compression Fields
Yixin Gao, Xiaohan Pan, Xin Li +1
The rapid development of AIGC foundation models has revolutionized the paradigm of image compression, which paves the way for the abandonment of most pixel-level transform and codi…
Towards Defining an Efficient and Expandable File Format for AI-Generated Contents
Yixin Gao, Runsen Feng, Xin Li +2
Recently, AI-generated content (AIGC) has gained significant traction due to its powerful creation capability. However, the storage and transmission of large amounts of high-qualit…
Image Coding for Machines with Omnipotent Feature Learning
Ruoyu Feng, Xin Jin, Zongyu Guo +6
Image Coding for Machines (ICM) aims to compress images for AI tasks analysis rather than meeting human perception. Learning a kind of feature that is both general (for AI tasks) a…