4 citations · 4 across the 4 of their papers we have counts for
4 papers
Tele-Omni: a Unified Multimodal Framework for Video Generation and Editing
Jialun Liu, Tian Li, Xiao Cao +20
Recent advances in diffusion-based video generation have substantially improved visual fidelity and temporal coherence. However, most existing approaches remain task-specific and r…
SemiDDM-Weather: A Semi-supervised Learning Framework for All-in-one Adverse Weather Removal
Fang Long, Wenkang Su, Zixuan Li +4
Adverse weather removal aims to restore clear vision under adverse weather conditions. Existing methods are mostly tailored for specific weather types and rely heavily on extensive…
CLIPVQA:Video Quality Assessment via CLIP
Fengchuang Xing, Mingjie Li, Yuan-Gen Wang +2
In learning vision-language representations from web-scale data, the contrastive language-image pre-training (CLIP) mechanism has demonstrated a remarkable performance in many visi…
Chat-UniVi: Unified Visual Representation Empowers Large Language Models with Image and Video Understanding
Peng Jin, Ryuichi Takanobu, Wancai Zhang +2
Large language models have demonstrated impressive universal capabilities across a wide range of open-ended tasks and have extended their utility to encompass multimodal conversati…