6 papers
Navigating User Behavior toward Personalized Multimodal Generation
Hengji Zhou, Yufeng Liu, Ye Liu +3
Modern AIGC pipelines deliver high-fidelity images and videos but presuppose a well-formed creation instruction, while end users rarely articulate visual details, leaving generator…
TailorMind: Towards Preference-Aligned Multimodal Content Generation
Hengji Zhou, Ye Liu, Yufeng Liu +3
Personalized content systems depend on available UGC and struggle when suitable content is absent, delayed, or costly to create. Although multimodal generators can synthesize conte…
VideoMind: A Chain-of-LoRA Agent for Temporal-Grounded Video Reasoning
Ye Liu, Kevin Qinghong Lin, Chang Wen Chen +1
Videos, with their unique temporal dimension, demand precise grounded understanding, where answers are directly linked to visual, interpretable evidence. Despite significant breakt…
UniPixel: Unified Object Referring and Segmentation for Pixel-Level Visual Reasoning
Ye Liu, Zongyang Ma, Junfu Pu +4
Recent advances in Large Multi-modal Models (LMMs) have demonstrated their remarkable success as general-purpose multi-modal assistants, with particular focuses on holistic image-…
A Survey on Video Temporal Grounding with Multimodal Large Language Model
Jianlong Wu, Wei Liu, Ye Liu +4
The recent advancement in video temporal grounding (VTG) has significantly enhanced fine-grained video understanding, primarily driven by multimodal large language models (MLLMs).…
TUNA: Comprehensive Fine-grained Temporal Understanding Evaluation on Dense Dynamic Videos
Fanheng Kong, Jingyuan Zhang, Hongzhi Zhang +7
Videos are unique in their integration of temporal elements, including camera, scene, action, and attribute, along with their dynamic relationships over time. However, existing ben…