5 citations · 5 across the 9 of their papers we have counts for
5 papers · 1 filter
CrossVid: A Comprehensive Benchmark for Evaluating Cross-Video Reasoning in Multimodal Large Language Models
Jingyao Li, Jingyun Wang, Molin Tan +6
Cross-Video Reasoning (CVR) presents a significant challenge in video understanding, which requires simultaneous understanding of multiple videos to aggregate and compare informati…
LTCA: Long-range Temporal Context Attention for Referring Video Object Segmentation
Cilin Yan, Jingyun Wang, Guoliang Kang
Referring Video Segmentation (RVOS) aims to segment objects in videos given linguistic expressions. The key to solving RVOS is to extract long-range temporal context information fr…
USB-Rec: An Effective Framework for Improving Conversational Recommendation Capability of Large Language Model
Jianyu Wen, Jingyun Wang, Cilin Yan +3
Recently, Large Language Models (LLMs) have been widely employed in Conversational Recommender Systems (CRSs). Unlike traditional language model approaches that focus on training,…
Rethinking the Global Knowledge of CLIP in Training-Free Open-Vocabulary Semantic Segmentation
Jingyun Wang, Cilin Yan, Guoliang Kang
Recent works modify CLIP to perform open-vocabulary semantic segmentation in a training-free manner (TF-OVSS). In vanilla CLIP, patch-wise image representations mainly encode homog…
Separate Motion from Appearance: Customizing Motion via Customizing Text-to-Video Diffusion Models
Huijie Liu, Jingyun Wang, Shuai Ma +3
Motion customization aims to adapt the diffusion model (DM) to generate videos with the motion specified by a set of video clips with the same motion concept. To realize this goal,…