collaborators

5 papers

cs.CV2026

When Physical Preferences Meet Semantic Constraints: Physical and Semantic Direct Preference Optimization for Text-to-Video Generation

Siwei Meng, Yawei Luo, Shu Zhang +1

Text-to-video (T2V) generation models have achieved strong visual realism, but improving physical plausibility can come at the cost of semantic consistency with the input text. Thi…

cs.CV2026

EchoFoley: Event-Centric Hierarchical Control for Video Grounded Creative Sound Generation

Bingxuan Li, Yiming Cui, Yicheng He +4

Sound effects build an essential layer of multimodal storytelling, shaping the emotional atmosphere and the narrative semantics of videos. Despite recent advancement in video-text-…

cs.CV2026

Referring Layer Decomposition

Fangyi Chen, Yaojie Shen, Lu Xu +4

Precise, object-aware control over visual content is essential for advanced image editing and compositional generation. Yet, most existing approaches operate on entire images holis…

cs.CV2026

Vidi2.5: Large Multimodal Models for Video Understanding and Creation

Vidi Team, Chia-Wen Kuo, Chuang Huang +31

Video has emerged as the primary medium for communication and creativity on the Internet, driving strong demand for scalable, high-quality video production. Vidi models continue to…

cs.CV2025

xGen-MM (BLIP-3): A Family of Open Large Multimodal Models

Le Xue, Manli Shu, Anas Awadalla +30

This paper introduces BLIP-3, an open framework for developing Large Multimodal Models (LMMs). The framework comprises meticulously curated datasets, a training recipe, model archi…