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Found 2 papers, 1 papers with code
Learning Spatial-Temporal Regularized Tensor Sparse RPCA for Background Subtraction
Robust principal component analysis has been identified as a promising unsupervised paradigm for background subtraction tasks in the last decade thanks to its competitive performance in a number of benchmark datasets.
Improving Underwater Visual Tracking With a Large Scale Dataset and Image Enhancement
The method has resulted in a significant performance improvement, of up to 5. 0% AUC, of state-of-the-art (SOTA) visual trackers.
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