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Rgb T Tracking On Lasher

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Precision
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Results

Performance results of various models on this benchmark

Paper Title
SUTrack-L38476.961.9SUTrack: Towards Simple and Unified Single Object Tracking
SeqTrackv2-L38476.761.0Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
PromptTrack76.260.7-
STTrack76.060.3Exploiting Multimodal Spatial-temporal Patterns for Video Object Tracking
SeqTrackv2-L25674.158.8Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
APTrack74.158.9Adaptive Perception for Unified Visual Multi-modal Object Tracking
CKD73.258.1Breaking Modality Gap in RGBT Tracking: Coupled Knowledge Distillation
CFBT73.258.4Cross Fusion RGB-T Tracking with Bi-directional Adapter
MambaVT-S25673.057.9MambaVT: Spatio-Temporal Contextual Modeling for robust RGB-T Tracking
MST73.058.8-
MambaVT-M25672.757.5MambaVT: Spatio-Temporal Contextual Modeling for robust RGB-T Tracking
MoETrack72.157.8Revisiting RGBT Tracking Benchmarks from the Perspective of Modality Validity: A New Benchmark, Problem, and Solution
MPLT72.057.1RGB-T Tracking via Multi-Modal Mutual Prompt Learning
SeqTrackv2-B38471.556.2Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
CSTNet71.557.2Transformer-based RGB-T Tracking with Channel and Spatial Feature Fusion
MMMP71.456.7From Two-Stream to One-Stream: Efficient RGB-T Tracking via Mutual Prompt Learning and Knowledge Distillation
GMMT70.756.6Generative-based Fusion Mechanism for Multi-Modal Tracking
SeqTrackv2-B25670.455.8Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
AFter70.355.1AFter: Attention-based Fusion Router for RGBT Tracking
TBSI70.256.5Bridging Search Region Interaction With Template for RGB-T Tracking
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Rgb T Tracking On Lasher | SOTA | HyperAI