Hybrid ANN-CANN network for visual object tracking that operationalizes bias-variance complementarity to outperform baselines on nine benchmarks.
In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp
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LGTrack achieves 258.7 FPS real-time UAV tracking with 82.8% precision on UAVDT by combining dynamic layer selection, Global-Grouped Coordinate Attention, and Similarity-Guided Layer Adaptation.
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A Theory-grounded Hybrid Neural Network Integrating Complementary Estimation Mechanisms for Stable Visual Object TrackingA
Hybrid ANN-CANN network for visual object tracking that operationalizes bias-variance complementarity to outperform baselines on nine benchmarks.
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Layer-Guided UAV Tracking: Enhancing Efficiency and Occlusion Robustness
LGTrack achieves 258.7 FPS real-time UAV tracking with 82.8% precision on UAVDT by combining dynamic layer selection, Global-Grouped Coordinate Attention, and Similarity-Guided Layer Adaptation.