3 papers
cs.CV2026
VideoAfford: Grounding 3D Affordance from Human-Object-Interaction Videos via Multimodal Large Language Model
Hanqing Wang, Mingyu Liu, Xiaoyu Chen +9
3D affordance grounding aims to highlight the actionable regions on 3D objects, which is crucial for robotic manipulation. Previous research primarily focused on learning affordanc…
cs.CV2025
Learning to Tell Apart: Weakly Supervised Video Anomaly Detection via Disentangled Semantic Alignment
Wenti Yin, Huaxin Zhang, Xiang Wang +7
Recent advancements in weakly-supervised video anomaly detection have achieved remarkable performance by applying the multiple instance learning paradigm based on multimodal founda…
cs.CV2025
DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample
Wenting Yin, Han Sun, Xinru Meng +2
Continual test-time adaptation aims to continuously adapt a pre-trained model to a stream of target domain data without accessing source data. Without access to source domain data,…