1 citations · 1 across the 6 of their papers we have counts for
8 papers
Vehicle-centric Perception via Multimodal Structured Pre-training
Wentao Wu, Xiao Wang, Chenglong Li +2
Vehicle-centric perception plays a crucial role in many intelligent systems, including large-scale surveillance systems, intelligent transportation, and autonomous driving. Existin…
Pedestrian Attribute Recognition via Hierarchical Cross-Modality HyperGraph Learning
Xiao Wang, Shujuan Wu, Xiaoxia Cheng +3
Current Pedestrian Attribute Recognition (PAR) algorithms typically focus on mapping visual features to semantic labels or attempt to enhance learning by fusing visual and attribut…
Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute Recognition
Weizhe Kong, Xiao Wang, Ruichong Gao +5
Pedestrian Attribute Recognition (PAR) is an indispensable task in human-centered research and has made great progress in recent years with the development of deep neural networks.…
CM3AE: A Unified RGB Frame and Event-Voxel/-Frame Pre-training Framework
Wentao Wu, Xiao Wang, Chenglong Li +4
Event cameras have attracted increasing attention in recent years due to their advantages in high dynamic range, high temporal resolution, low power consumption, and low latency. S…
Breaking Shallow Limits: Task-Driven Pixel Fusion for Gap-free RGBT Tracking
Andong Lu, Yuanzhi Guo, Wanyu Wang +3
Current RGBT tracking methods often overlook the impact of fusion location on mitigating modality gap, which is key factor to effective tracking. Our analysis reveals that shallowe…
Towards General Multimodal Visual Tracking
Andong Lu, Mai Wen, Jinhu Wang +4
Existing multimodal tracking studies focus on bi-modal scenarios such as RGB-Thermal, RGB-Event, and RGB-Language. Although promising tracking performance is achieved through lever…