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MambaRefine-CD: MambaVision with Region-Boundary Temporal Refinement

arXiv 2607.04403 ↗First posted 5 Jul 2026eess.IV cs.CVcited by 0

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Abstract (arXiv)

Binary change detection in remote sensing requires both complete changed-region localization and accurate boundary delineation. We present MambaRefine-CD, a region-boundary temporal refinement framework built on a shared MambaVision encoder. The proposed D-RBI module constructs temporal evidence from paired features, absolute differences, and signed differences, then separates it into region and Sobel-conditioned boundary streams. Region features are enhanced with CRAM-lite and decoded by an adaptive receptive-field FPN, while the finest boundary stream guides a bounded residual refinement of the coarse prediction. Experiments on DSIFN-CD and WHU-CD show strong changed-class F1 and IoU under verified evaluation settings, and ablations support the contribution of signed temporal evidence and the full region-boundary refinement pipeline.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 15 of its 22 references that are in the map. First posted on arXiv 5 Jul 2026.

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15 of 22 references.

References · 15

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  2. 2023Mamba: Linear-Time Sequence Modeling with Selective State Spacescited by 4,616
  3. 2024VMamba: Visual State Space Modelcited by 955
  4. 2018Fully Convolutional Siamese Networks for Change Detectioncited by 305
  5. 2021Remote Sensing Image Change Detection with Transformerscited by 305
  6. 2022A Transformer-Based Siamese Network for Change Detectioncited by 243
  7. 2024MambaVision: A Hybrid Mamba-Transformer Vision Backbonecited by 222
  8. 2018Boundary loss for highly unbalanced segmentationcited by 187
  9. 2019Gated-SCNN: Gated Shape CNNs for Semantic Segmentationcited by 165
  10. 2024ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Modelcited by 118
  11. 2020DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite imagescited by 75
  12. 2025Enhanced SCanNet with CBAM and Dice Loss for Semantic Change Detectioncited by 3
3 more
  1. 2025Precision Spatio-Temporal Feature Fusion for Robust Remote Sensing Change Detectioncited by 3
  2. 2026A Controlled Benchmark of Visual State-Space Backbones with Domain-Shift and Boundary Analysis for Remote-Sensing Segmentationcited by 2
  3. 2025Mamba-FCS: Joint Spatio- Frequency Feature Fusion, Change-Guided Attention, and SeK Loss for Enhanced Semantic Change Detection in Remote Sensingcited by 1

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