6 papers
Parameter-Dynamic Adaptive Fusion and Calibration Network for RGBT Tracking
Zhaoding Ding, Chenglong Li, Jiandong Jin +2
Existing RGBT trackers typically employ fusion functions with fixed parameters across different targets and scenarios. Although dynamic-architecture methods improve fusion flexibil…
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…
Cross-Modal UAV Object Tracking: State-Aware Representation Learning and A Unified Benchmark
Yun Xiao, Zhihong Hong, Jiandong Jin +3
Unmanned Aerial Vehicle (UAV) object tracking has emerged as a popular research field with broad practical applications. Modern UAVs are increasingly equipped with both visible lig…
SequencePAR: Understanding Pedestrian Attributes via A Sequence Generation Paradigm
Jiandong Jin, Xiao Wang, Yin Lin +4
Current pedestrian attribute recognition (PAR) algorithms use multi-label or multi-task learning frameworks with specific classification heads. These models often struggle with imb…
RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion Framework
Xiao Wang, Haiyang Wang, Shiao Wang +5
Existing pedestrian attribute recognition methods are generally developed based on RGB frame cameras. However, these approaches are constrained by the limitations of RGB cameras, s…
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…