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Rgb-T Tracking

RGBT tracking, or RGB-Thermal tracking, is a sophisticated method utilized in computer vision for tracking objects across both RGB and thermal infrared modalities. This technique combines information from both RGB and thermal imagery to enhance object detection and tracking performance, particularly in challenging environments where lighting conditions may vary or be limited. By integrating data from these two modalities, RGBT tracking systems can effectively compensate for the limitations of each individual modality, such as the inability of RGB cameras to capture clear images in low-light or adverse weather conditions, and the inability of thermal cameras to accurately identify object details. RGBT tracking algorithms typically involve sophisticated fusion techniques to combine information from RGB and thermal sensors, enabling robust and accurate object tracking in diverse scenarios ranging from surveillance and security applications to autonomous vehicles and search and rescue operations.

Papers

Showing 2130 of 55 papers

TitleStatusHype
LasHeR: A Large-scale High-diversity Benchmark for RGBT TrackingCode1
Multi-modal Visual Tracking: Review and Experimental ComparisonCode1
Lightweight RGB-T Tracking with Mobile Vision Transformers0
Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T TrackingCode0
Breaking Shallow Limits: Task-Driven Pixel Fusion for Gap-free RGBT Tracking0
Adaptive Perception for Unified Visual Multi-modal Object Tracking0
BTMTrack: Robust RGB-T Tracking via Dual-template Bridging and Temporal-Modal Candidate Elimination0
PURA: Parameter Update-Recovery Test-Time Adaption for RGB-T Tracking0
Cross Fusion RGB-T Tracking with Bi-directional Adapter0
RGBT Tracking via All-layer Multimodal Interactions with Progressive Fusion Mamba0
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