6 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…
Segment Any Vehicle: Semantic and Visual Context Driven SAM and A Benchmark
Xiao Wang, Ziwen Wang, Wentao Wu +4
With the rapid advancement of autonomous driving, vehicle perception, particularly detection and segmentation, has placed increasingly higher demands on algorithmic performance. Pr…
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.…
DehazeMamba: SAR-guided Optical Remote Sensing Image Dehazing with Adaptive State Space Model
Zhicheng Zhao, Jinquan Yan, Chenglong Li +2
Optical remote sensing image dehazing presents significant challenges due to its extensive spatial scale and highly non-uniform haze distribution, which traditional single-image de…
Large Language Model Guided Progressive Feature Alignment for Multimodal UAV Object Detection
Wentao Wu, Chenglong Li, Xiao Wang +2
Existing multimodal UAV object detection methods often overlook the impact of semantic gaps between modalities, which makes it difficult to achieve accurate semantic and spatial al…
An Empirical Study of Mamba-based Pedestrian Attribute Recognition
Xiao Wang, Weizhe Kong, Jiandong Jin +5
Current strong pedestrian attribute recognition models are developed based on Transformer networks, which are computationally heavy. Recently proposed models with linear complexity…