/awesome-infrared-small-targets

List of awesome infrared small targets detection methods!

MIT LicenseMIT

Awesome Infrared Small Targets

Awesome

Table of Contents

  • Tophat, Morphology-based algorithm for point target detection in infrared backgrounds.

    • Tom V T, Peli T, Leung M, et al. Signal and Data Processing of Small Targets, 1993. International Society for Optics and Photonics, 1993.
  • MaxMedian, Max-mean and max-median filters for detection of small targets.

    • Deshpande S D, Er M H, Venkateswarlu R, et al. Signal and Data Processing of Small Targets, 1999. International Society for Optics and Photonics, 1999.
  • PFT, Spatio-temporal saliency detection using phase spectrum of Quaternion Fourier Transform.

    • Guo C, Ma Q, Zhang L. CVPR, 2008.
  • LACM-LSK, Robust infrared small target detection using local steering kernel reconstruction.

    • Li Y, Zhang Y. Pattern Recognition, 2018.
  • Infrared Small Target Detection by Density Peaks Searching and Maximum-Gray Region Growing.

    • Huang S, Peng Z, Wang Z, et al. TGRS Letters, 2019.
  • FKRW, Infrared Small Target Detection Based on Facet Kernel and Random Walker.

    • Y. Qin, L. Bruzzone, C. Gao and B. Li. TGRS, 2019.
  • Structure-Adaptive Clutter Suppression for Infrared Small Target Detection: Chain-Growth Filtering.

    • Huang S, Liu Y, He Y, et al. Remote Sensing, 2020.
  • Infrared small-target detection based on multiple morphological profiles.

    • M. Zhao, L. Li, W. Li, et al. TGRS, 2020.
  • LCM, A Local Contrast Method for Small Infrared Target Detection.

    • Chen C L P, Li H, Wei Y, et al. TGRS, 2013.
  • ILCM, A Robust Infrared Small Target Detection Algorithm Based on Human Visual System.

    • Han J, Ma Y, Zhou B, et al. TGRS Letters, 2014.
  • LSM, An Efficient Infrared Small Target Detection Method Based on Visual Contrast Mechanism.

    • Chen Y, Xin Y. TGRS Letters, 2016.
  • WLDM, Small infrared target detection based on weighted local difference measure.

    • Deng H, Sun X, Liu M, et al. TGRS, 2016.
  • IDoGb, An infrared small target detecting algorithm based on human visual system.

    • Han J, Ma Y, Huang J, et al. TGRS Letters, 2016.
  • NLCM, Effective infrared small target detection utilizing a novel local contrast method.

    • Qin Y, Li B. TGRS Letters, 2016.
  • MPCM, Multiscale patch-based contrast measure for small infrared target detection.

    • Wei Y, You X, Li H. Pattern Recognition, 2016.
  • LDM, Entropy-based window selection for detecting dim and small infrared targets.

    • Deng H, Sun X, Liu M, et al. Pattern Recognition, 2017.
  • DECM, Derivative entropy-based contrast measure for infrared small-target detection.

    • Bai X, Bi Y. TGRS, 2018.
  • RLCM, Infrared small target detection utilizing the multiscale relative local contrast measure.

    • Han J, Liang K, Zhou B, et al. TGRS Letters, 2018.
  • WMFD, Infrared small target detection based on flux density and direction diversity in gradient vector field.

    • Liu D, Cao L, Li Z, et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018.
  • HB-MLCM, High-boost-based multiscale local contrast measure for infrared small target detection.

    • Shi Y, Wei Y, Yao H, et al. TGRS Letters, 2017.
  • Infrared Small Target Detection Based on Derivative Dissimilarity Measure.

    • Cao X, Rong C, Bai X. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019.
  • Infrared Small Target Detection Via Center-surround Gray Difference Measure with Local Image Block Analysis.

    • Y. Li, Z. Li, Y. Shen and Z. Guo. TAES, 2022.
  • Weighted Local Ratio-Difference Contrast Method for Detecting an Infrared Small Target against Ground–Sky Background.

    • H. Wei, P. Ma, D. Pang et al. Remote Sensing, 2022.
  • IPI, Infrared patch-image model for small target detection in a single image.

    • Gao C, Meng D, Yang Y, et al. TIP, 2013.
  • NIPPS, Non-negative infrared patch-image model: Robust target-background separation via partial sum minimization of singular values.

    • Dai Y, Wu Y, Song Y, et al. Infrared Physics & Technology, 2017.
  • TV-PCP, Infrared dim target detection based on total variation regularization and principal component pursuit.

    • Wang X, Peng Z, Kong D, et al. Image and Vision Computing, 2017.
  • NRAM, Infrared small target detection via non-convex rank approximation minimization joint l2, 1 norm.

    • Zhang L, Peng L, Zhang T, et al. Remote Sensing, 2018.
  • NOLC, Infrared small target detection based on non-convex optimization with Lp-norm constraint.

    • Zhang T, Wu H, Liu Y, et al. Remote Sensing, 2019.
  • RS1/2NIPI, Detection of Small Target Using Schatten 1/2 Quasi-Norm Regularization with Reweighted Sparse Enhancement in Complex Infrared Scenes.

    • F. Zhou, Y. Wu, Y. Dai and P. Wang. Remote Sensing, 2019.
  • LRSR, Small infrared target detection based on low-rank and sparse representation.

    • He Y J, Li M, Zhang J L, et al. Infrared Physics & Technology, 2015.
  • SMSL, Infrared dim and small target detection based on stable multisubspace learning in heterogeneous scene.

    • Wang X, Peng Z, Kong D, et al. TGRS, 2017.
  • SRWS, Infrared small target detection via self-regularized weighted sparse model.

    • Zhang T, Peng Z, Wu H, et al. Neurocomputing, 2021.
  • RIPT, Reweighted infrared patch-tensor model with both nonlocal and local priors for single-frame small target detection.

    • Dai Y, Wu Y. IEEE journal of selected topics in applied earth observations and remote sensing, 2017.
  • PSTNN, Infrared small target detection based on partial sum of the tensor nuclear norm.

    • Zhang L, Peng Z. Remote Sensing, 2019.
  • TCTHR, Infrared Small Target Detection via Low-Rank Tensor Completion With Top-Hat Regularization.

    • H. Zhu, S. Liu, L. Deng, Y. Li and F. Xiao. TGRS, 2020.
  • METTR, Infrared dim target detection via mode-k1k2 extension tensor tubal rank under complex ocean environment.

    • Z. Cao, X. Kong, Q. Zhu, S. Cao and Z. Peng. ISPRS Journal of Photogrammetry and Remote Sensing, 2021.
  • LogTFNN, Infrared Small Target Detection via Nonconvex Tensor Fibered Rank Approximation.

    • X. Kong, C. Yang, S. Cao, C. Li, Z. Peng. TGRS, 2021.
  • CMPG, Infrared Small Target Detection via L0 Sparse Gradient Regularized Tensor Spectral Support Low-Rank Decomposition.

    • F. Zhou, M. Fu, Y. Duan et al. TAES, 2022.
  • STT: Small Target Detection in Infrared Videos Based on Spatio-Temporal Tensor Model.

    • H. -K. Liu, L. Zhang and H. Huang. TGRS, 2020.
  • ECA-STT: Edge and Corner Awareness-Based Spatial–Temporal Tensor Model for Infrared Small-Target Detection.

    • P. Zhang, L. Zhang, X. Wang, F. Shen, T. Pu and C. Fei. TGRS, 2022.
  • ASTTV-NTLA: Nonconvex Tensor Low-Rank Approximation for Infrared Small Target Detection.

    • T. Liu et al. TGRS, 2022.
  • IMNN-LWEC: A Novel Infrared Small Target Detection Based on Spatial–Temporal Tensor Model.

    • Y. Luo, X. Li, S. Chen et al. TGRS, 2022.
  • NPSTT, Infrared Small Target Detection Using Nonoverlapping Patch Spatial–Temporal Tensor Factorization With Capped Nuclear Norm Regularization.

    • G. Wang, B. Tao, X. Kong and Z. Peng. TGRS, 2022.
  • SRSTT, Sparse Regularization-Based Spatial-Temporal Twist Tensor Model for Infrared Small Target Detection.

    • J. Li, P. Zhang, L. Zhang and Z. Zhang. TGRS, 2023.
  • 4-D TT/TR, Infrared Small Target Detection Using Spatiotemporal 4-D Tensor Train and Ring Unfolding.

    • F. Wu, H. Yu, A. Liu, J. Luo and Z. Peng. TGRS, 2023.
  • WSWTNN-PnP, Combining Deep Denoiser and Low-rank Priors for Infrared Small Target Detection.

    • T. Liu, Q. Yin, J. Yang, Y. Wang and W. An. PR, 2023.
  • 3DSTPM, Infrared Small Target Detection Combining Deep Spatial–Temporal Prior With Traditional Priors.

    • Z. Zhang, P. Gao, S. Ji, X. Wang, and P. Zhang. TGRS, 2023.
  • MDvsFA cGan, Miss detection vs. false alarm: Adversarial learning for small object segmentation in infrared images.

    • Wang H, Zhou L, Wang L. ICCV, 2019.
  • ACM, Asymmetric contextual modulation for infrared small target detection.

    • Dai Y, Wu Y, Zhou F, et al. WACV, 2021.
  • TBC-Net: A real-time detector for infrared small target detection using semantic constraint.

    • M. Zhao, L. Cheng, X. Yang, P. Feng, L. Liu and N. Wu. arXiv, 2019
  • ALCNet, Attentional Local Contrast Networks for Infrared Small Target Detection.

    • Y. Dai, Y. Wu, F. Zhou, K. J. I. T. o. G. Barnard and R. Sensing. TGRS, 2021
  • DNANet, Dense Nested Attention Network for Infrared Small Target Detection.

    • B. Li, C. Xiao, L. Wang, Y. Wang, Z. Lin, M. Li, et al. TIP, 2022
  • Infrared Small-Dim Target Detection with Transformer under Complex Backgrounds

    • F. Liu, C. Gao, F. Chen, D. Meng, W. Zuo and X. Gao. TIP, 2023
  • EAAU-Net: Enhanced asymmetric attention U-Net for infrared small target detection.

    • X. Tong, B. Sun, J. Wei, Z. Zuo and S. Su. Remote Sensing, 2021
  • AGPCNet, Attention-Guided Pyramid Context Networks for Infrared Small Target Detection.

    • Tianfang Zhang, Lei Li, Siying Cao, Tian Pu, Zhenming Peng. TAES, 2023
  • IRSTFormer: A Hierarchical Vision Transformer for Infrared Small Target Detection.

    • G. Chen, W. Wang and S. Tan. Remote Sensing, 2022
  • APANet, Novel Asymmetric Pyramid Aggregation Network for Infrared Dim and Small Target Detection.

    • G. Lv, L. Dong, J. Liang and W. Xu. Remote Sensing, 2022
  • Prior-Guided Data Augmentation for Infrared Small Target Detection.

    • A. Wang, W. Li, Z. Huang et al. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
  • IAANet, Interior attention-aware network for infrared small target detection.

    • A. Wang, W. Li, Z. Huang et al. TGRS, 2022
  • ISNet: Shape matters for infrared small target detection.

    • M. Zhang, R. Zhang, Y. Yang et al. CVPR, 2022
  • UIUNet: U-Net in U-Net for Infrared Small Object Detection.

    • X. Wu, D. Hong, J. Chanussot. TIP, 2023
  • MTUNet: Multilevel TransUNet for Space-Based Infrared Tiny Ship Detection.

    • T. Wu et al. TGRS, 2023
  • LESPS: Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection with Single Point Supervision.

    • X. Ying et al. CVPR, 2023
  • RDIAN, Receptive-Field and Direction Induced Attention Network for Infrared Dim Small Target Detection With a Large-Scale Dataset IRDST.

    • H. Sun, J. Bai, F. Yang and X. Bai. TGRS, 2023
  • Monte Carlo Linear Clustering with Single-Point Supervision is Enough for Infrared Small Target Detection

    • B. Li et al. ICCV, 2023
  • A Spatial-Temporal Feature-Based Detection Framework for Infrared Dim Small Target.

    • J. Du et al. TGRS, 2022
  • STDMANet: Spatio-Temporal Differential Multiscale Attention Network for Small Moving Infrared Target Detection.

    • P. Yan, R. Hou, X. Duan, C. Yue, X. Wang, and X. Cao. TGRS, 2023
  • SSTNet: Sliced Spatio-Temporal Network With Cross-Slice ConvLSTM for Moving Infrared Dim-Small Target Detection.

    • S. Chen, L. Ji, J. Zhu, M. Ye, and X. Yao. TGRS, 2024
  • ST-Trans: Spatial-Temporal Transformer for Infrared Small Target Detection in Sequential Images.

    • X. Tong et al. TGRS, 2024
  • Direction-Coded Temporal U-Shape Module for Multiframe Infrared Small Target Detection.

    • R. Li et al. TNNLS, 2023
  • RPCANet: Deep Unfolding RPCA Based Infrared Small Target Detection.
    • F. Wu, T. Zhang, L. Li, Y. Huang, and Z. Peng. WACV, 2024
  • MDFA, Miss detection vs. false alarm: Adversarial learning for small object segmentation in infrared images.

    • Wang H, Zhou L, Wang L. ICCV, 2019.
  • SIRST, Asymmetric contextual modulation for infrared small target detection.

    • Dai Y, Wu Y, Zhou F, et al. WACV, 2021.
  • SIRST-Aug, Attention-Guided Pyramid Context Networks for Infrared Small Target Detection.

    • Tianfang Zhang, Lei Li, Siying Cao, Tian Pu, Zhenming Peng. TAES, 2023
  • NUDT-SIRST, Dense Nested Attention Network for Infrared Small Target Detection.

    • B. Li, C. Xiao, L. Wang, Y. Wang, Z. Lin, M. Li, et al. TIP, 2022
  • IRSTD-1k: Shape matters for infrared small target detection.

    • M. Zhang, R. Zhang, Y. Yang et al. CVPR, 2022

Note:

  • represents offical code.
  • represents reproduced code.