4 papers
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…
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…
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…
Enhancing Multimodal Large Language Models with Multi-instance Visual Prompt Generator for Visual Representation Enrichment
Wenliang Zhong, Wenyi Wu, Qi Li +6
Multimodal Large Language Models (MLLMs) have achieved SOTA performance in various visual language tasks by fusing the visual representations with LLMs leveraging some visual adapt…