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Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision.

, , , , , , , and . CVPR, page 15528-15538. IEEE, (2023)

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Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection., , , , , , , and . ICCV, page 1009-1019. IEEE, (2023)Learning Sparse Masks for Efficient Image Super-Resolution., , , , , , and . CoRR, (2020)Detecting Dim Small Target in Infrared Images via Subpixel Sampling Cuneate Network., , , , and . IEEE Geosci. Remote. Sens. Lett., (2022)Exploring Sparsity in Image Super-Resolution for Efficient Inference., , , , , , and . CVPR, page 4917-4926. Computer Vision Foundation / IEEE, (2021)A Constrained Sparse-Representation-Based Binary Hypothesis Model for Target Detection in Hyperspectral Imagery., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 12 (6): 1933-1947 (2019)Robust Infrared Small Target Detection Using Multiscale Gray and Variance Difference Measures., , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 11 (12): 5039-5052 (2018)Dense Nested Attention Network for Infrared Small Target Detection., , , , , , , and . CoRR, (2021)Fast multi-frame image super-resolution based on MRF., , , and . CoRR, (2017)Infrared Small Target Detection Using a Temporal Variance and Spatial Patch Contrast Filter., , and . IEEE Access, (2019)FSVO: Semi-direct monocular visual odometry using fixed maps., , , and . ICIP, page 2553-2557. IEEE, (2017)