mlsanityData to 7 Oct 2026

A Mamba-based Siamese Network for Remote Sensing Change Detection

arXiv 2407.06839 ↗First posted 8 Jul 2024cs.CVcited by 13

On the map: State-space sequence models (S4, Mamba) → Point clouds, detection and remote sensing

Abstract (arXiv)

Change detection in remote sensing images is an essential tool for analyzing a region at different times. It finds varied applications in monitoring environmental changes, man-made changes as well as corresponding decision-making and prediction of future trends. Deep learning methods like Convolutional Neural Networks (CNNs) and Transformers have achieved remarkable success in detecting significant changes, given two images at different times. In this paper, we propose a Mamba-based Change Detector (M-CD) that segments out the regions of interest even better. Mamba-based architectures demonstrate linear-time training capabilities and an improved receptive field over transformers. Our experiments on four widely used change detection datasets demonstrate significant improvements over existing state-of-the-art (SOTA) methods. Our code and pre-trained models are available at https://github.com/JayParanjape/M-CD

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Placed in Point clouds, detection and remote sensing, one of 10 directions in State-space sequence models (S4, Mamba). Builds on 34 of its 72 references that are in the map. First posted on arXiv 8 Jul 2024.

Builds on

34 of 72 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection6 Jun
  2. 2024ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model4 Apr
  3. 2024PointMamba: A Simple State Space Model for Point Cloud Analysis16 Feb

Other references · 31

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  5. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,267
  6. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  7. 2016Densely Connected Convolutional Networkscited by 6,691
  8. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
  9. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  10. 2018CBAM: Convolutional Block Attention Modulecited by 2,463
  11. 2021Efficiently Modeling Long Sequences with Structured State Spacescited by 2,424
  12. 2018UNet++: A Nested U-Net Architecture for Medical Image Segmentationcited by 1,518
19 more
  1. 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Modelcited by 1,051
  2. 2021Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layerscited by 607
  3. 2020Dense Contrastive Learning for Self-Supervised Visual Pre-Trainingcited by 512
  4. 2024U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentationcited by 412
  5. 2024MambaIR: A Simple Baseline for Image Restoration with State-Space Modelcited by 349
  6. 2018Fully Convolutional Siamese Networks for Change Detectioncited by 305
  7. 2021Remote Sensing Image Change Detection with Transformerscited by 305
  8. 2022A Transformer-Based Siamese Network for Change Detectioncited by 243
  9. 2021Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Datacited by 214
  10. 2023Selective Structured State-Spaces for Long-Form Video Understandingcited by 105
  11. 2019Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Modelcited by 84
  12. 2024Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentationcited by 71
  13. 2022Efficient Movie Scene Detection using State-Space Transformerscited by 51
  14. 2020Deep Learning for Change Detection in Remote Sensing Images: Comprehensive Review and Meta-Analysiscited by 34
  15. 2024Weak-Mamba-UNet: Visual Mamba Makes CNN and ViT Work Better for Scribble-based Medical Image Segmentationcited by 29
  16. 2019Unsupervised Image Regression for Heterogeneous Change Detectioncited by 21
  17. 2022DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detectioncited by 19
  18. 2022Semantic-aware Dense Representation Learning for Remote Sensing Image Change Detectioncited by 16
  19. 2021Contrastive Multiview Coding with Electro-optics for SAR Semantic Segmentationcited by 14

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 7.

13 papers.

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By area:

  1. 2025Referring Change Detection in Remote Sensing Imagerycited by 6
  2. 2026NeXt2Former-CD: Efficient Remote Sensing Change Detection with Modern Vision Architecturescited by 3
  3. 20253D-SSM: A Novel 3D Selective Scan Module for Remote Sensing Change Detectioncited by 2
  4. 2025Information-Bottleneck Driven Binary Neural Network for Change Detectioncited by 2
  5. 2025ChessMamba: Structure-Aware Interleaving of State Spaces for Change Detection in Remote Sensing Imagescited by 1
  6. 2026Remote Sensing Change Detection via Weak Temporal Supervisioncited by 1
  7. 2025Operational Change Detection for Geographical Information: Overview and Challengescited by 0
  8. 2025Exploring Generalizable Pre-training for Real-world Change Detection via Geometric Estimationcited by 0
  9. 2026FAF-CD: Frequency-Aware Fusion for Change Detection under Imperfect Multimodal Remote Sensingcited by 0
  10. 2026State Space Models Meet Remote Sensing: A Surveycited by 0
  11. 2026JL1-CC&QA: Extending the JL1-CD Benchmark with Change Captioning and Question Answeringcited by 0
  12. 2026Learning Woody Clearing With Loss Alignment for Zero-Shot Regrowth and Woody Segmentationcited by 0
1 more
  1. 2026Temporally Ordered Region-Token Mamba with Logit-Space Diffusion for Remote Sensing Change Detectioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 20252DMCG:2DMambawith Change Flow Guidance for Change Detection in Remote Sensing
  2. 2025Efficient Remote Sensing Change Detection with Change State Space Models
  3. 2025Mamba-FCS: Joint Spatio- Frequency Feature Fusion, Change-Guided Attention, and SeK Loss for Enhanced Semantic Change Detection in Remote Sensing
  4. 2025Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detection
  5. 2025Vision Mamba in Remote Sensing: A Comprehensive Survey of Techniques, Applications and Outlook
  6. 2025AtrousMamaba: An Atrous-Window Scanning Visual State Space Model for Remote Sensing Change Detection
  7. 2025DC-Mamba: Bi-temporal deformable alignment and scale-sparse enhancement for remote sensing change detection
  8. 2024ChangeAnywhere: Sample Generation for Remote Sensing Change Detection via Semantic Latent Diffusion Model