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20242026
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cs.CV2026

Spatio-Temporal Conditional Denoising Transformer for Modality-Missing RGBT Tracking

Andong Lu, Ziyi Zha, Jiandong Jin +4

Missing modalities in RGBT tracking often lead to incomplete and unstable multimodal feature representations that greatly degrade the performance. Existing methods typically attemp…

cs.CV2026

Graph-based Semantic Calibration Network for Unaligned UAV RGBT Image Semantic Segmentation and A Large-scale Benchmark

Fangqiang Fan, Zhicheng Zhao, Xiaoliang Ma +2

Fine-grained RGBT image semantic segmentation is crucial for all-weather unmanned aerial vehicle (UAV) scene understanding. However, UAV RGBT image semantic segmentation faces two…

cs.CV2026

Cross-modal Fuzzy Alignment Network for Text-Aerial Person Retrieval and A Large-scale Benchmark

Yifei Deng, Chenglong Li, Yuyang Zhang +2

Text-aerial person retrieval aims to identify targets in UAV-captured images from eyewitness descriptions, supporting intelligent transportation and public security applications. C…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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.…