5 papers
HUG-VIS: A Multimodal Benchmark for Human-centered Understanding and Generation in Visual Intelligence
Fei Ma, Zebang Cheng, Minghui Li +11
Visual intelligence seeks to perceive, interpret, and synthesize the visual world and is central to modern computer vision. Human-centered visual intelligence is especially demandi…
HOIMask: Towards Generative Masked Modeling for Human Object Interaction Generation
Yihong Ji, Jinsong Zhang, He Hu +1
Diffusion-based methods have dominated the HOI generation, as they enable critical contact fusions or signals to guide the diffusion process. However, they often result in high art…
MOPDA: Mixed-Trajectory On-Policy Distillation for Language-Guided Industrial Anomaly Detection
Shuimu Chen, Jing Jin, Nan Su +5
Large vision-language models (LVLMs) have shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judgments and interpretable reasoning. Howe…
Enhancing Long Video Question Answering with Scene-Localized Frame Grouping
Xuyi Yang, Wenhao Zhang, Hongbo Jin +5
Current Multimodal Large Language Models (MLLMs) often perform poorly in long video understanding, primarily due to resource limitations that prevent them from processing all video…
EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
He Hu, Lianzhong You, Hongbo Xu +7
With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (EI) capabilities is essential for enabl…