5 papers
SMTT: Novel Structured Multi-task Tracking with Graph-Regularized Sparse Representation for Robust Thermal Infrared Target Tracking
Shang Zhang, HuiPan Guan, XiaoBo Ding +2
Thermal infrared target tracking is crucial in applications such as surveillance, autonomous driving, and military operations. In this paper, we propose a novel tracker, SMTT, whic…
STARS: Sparse Learning Correlation Filter with Spatio-temporal Regularization and Super-resolution Reconstruction for Thermal Infrared Target Tracking
Shang Zhang, Xiaobo Ding, Huanbin Zhang +2
Thermal infrared (TIR) target tracking methods often adopt the correlation filter (CF) framework due to its computational efficiency. However, the low resolution of TIR images, alo…
DCFG: Diverse Cross-Channel Fine-Grained Feature Learning and Progressive Fusion Siamese Tracker for Thermal Infrared Target Tracking
Ruoyan Xiong, Yuke Hou, Princess Retor Torboh +6
To address the challenge of capturing highly discriminative features in ther-mal infrared (TIR) tracking, we propose a novel Siamese tracker based on cross-channel fine-grained fea…
FGSGT: Saliency-Guided Siamese Network Tracker Based on Key Fine-Grained Feature Information for Thermal Infrared Target Tracking
Ruoyan Xiong, Huanbin Zhang, Shentao Wang +6
Thermal infrared (TIR) images typically lack detailed features and have low contrast, making it challenging for conventional feature extraction models to capture discriminative tar…
RAMCT: Novel Region-adaptive Multi-channel Tracker with Iterative Tikhonov Regularization for Thermal Infrared Tracking
Shang Zhang, Yuke Hou, Guoqiang Gong +2
Correlation filter (CF)-based trackers have gained significant attention for their computational efficiency in thermal infrared (TIR) target tracking. However, ex-isting methods st…