activity
20242026
most citedPedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented Framework

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

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…

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

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…

cs.CV2025

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…

cs.CV20242 cited

Pedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented Framework

Jiandong Jin, Xiao Wang, Qian Zhu +2

Pedestrian Attribute Recognition (PAR) is one of the indispensable tasks in human-centered research. However, existing datasets neglect different domains (e.g., environments, times…