3 papers
cs.CV2026
Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs
Qi Li, Yanzhe Zhao, Yongxin Zhou +4
Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various modalities for a given query. Ho…
cs.CV2026
A Paradigm Shift: Fully End-to-End Training for Temporal Sentence Grounding in Videos
Allen He, Qi Liu, Kun Liu +2
Temporal sentence grounding in videos (TSGV) aims to localize a temporal segment that semantically corresponds to a sentence query from an untrimmed video. Most current methods ado…
cs.CV2025
HOIGen-1M: A Large-scale Dataset for Human-Object Interaction Video Generation
Kun Liu, Qi Liu, Xinchen Liu +5
Text-to-video (T2V) generation has made tremendous progress in generating complicated scenes based on texts. However, human-object interaction (HOI) often cannot be precisely gener…