LoHGNet combines Lorentz geometric encoding with high-order hypergraph relation learning to achieve competitive accuracy in infrared small target detection on complex backgrounds.
Receptive-field and direction induced attention network for infrared dim small target detection with a large-scale dataset irdst
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FeedbackSTS-Det improves moving infrared small target detection accuracy and reduces false alarms via a closed-loop spatio-temporal semantic feedback strategy and an embedded sparse semantic module that captures long-range dependencies with low overhead.
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LoHGNet: Infrared Small Target Detection through Lorentz Geometric Encoding with High-Order Relation Learning
LoHGNet combines Lorentz geometric encoding with high-order hypergraph relation learning to achieve competitive accuracy in infrared small target detection on complex backgrounds.
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FeedbackSTS-Det: Sparse Frames-Based Spatio-Temporal Semantic Feedback Network for Moving Infrared Small Target Detection
FeedbackSTS-Det improves moving infrared small target detection accuracy and reduces false alarms via a closed-loop spatio-temporal semantic feedback strategy and an embedded sparse semantic module that captures long-range dependencies with low overhead.