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cs.CV2026

Action Hints: Semantic Typicality and Context Uniqueness for Generalizable Skeleton-based Video Anomaly Detection

Canhui Tang, Sanping Zhou, Haoyue Shi +1

Zero-Shot Video Anomaly Detection (ZS-VAD) requires temporally localizing anomalies without target domain training data, which is a crucial task due to various practical concerns,…

cs.CV2026

Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection

Canhui Tang, Sanping Zhou, Yizhe Li +2

With the wide application of knowledge distillation between an ImageNet pre-trained teacher model and a learnable student model, unsupervised anomaly detection has witnessed a sign…

cs.CV2025

HumanSense: From Multimodal Perception to Empathetic Context-Aware Responses through Reasoning MLLMs

Zheng Qin, Ruobing Zheng, Yabing Wang +4

While Multimodal Large Language Models (MLLMs) show immense promise for achieving truly human-like interactions, progress is hindered by the lack of fine-grained evaluation framewo…

cs.CV2025

UniLayDiff: A Unified Diffusion Transformer for Content-Aware Layout Generation

Zeyang Liu, Le Wang, Sanping Zhou +4

Content-aware layout generation is a critical task in graphic design automation, focused on creating visually appealing arrangements of elements that seamlessly blend with a given…

cs.CV2025

SAMPO:Scale-wise Autoregression with Motion PrOmpt for generative world models

Sen Wang, Jingyi Tian, Le Wang +7

World models allow agents to simulate the consequences of actions in imagined environments for planning, control, and long-horizon decision-making. However, existing autoregressive…

cs.CV2025

Embracing Aleatoric Uncertainty: Generating Diverse 3D Human Motion

Zheng Qin, Yabing Wang, Minghui Yang +3

Generating 3D human motions from text is a challenging yet valuable task. The key aspects of this task are ensuring text-motion consistency and achieving generation diversity. Alth…