Non-Registration Change Detection: A Novel Change Detection Task and Benchmark Dataset
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Abstract (arXiv)
In this study, we propose a novel remote sensing change detection task, non-registration change detection, to address the increasing number of emergencies such as natural disasters, anthropogenic accidents, and military strikes. First, in light of the limited discourse on the issue of non-registration change detection, we systematically propose eight scenarios that could arise in the real world and potentially contribute to the occurrence of non-registration problems. Second, we develop distinct image transformation schemes tailored to various scenarios to convert the available registration change detection dataset into a non-registration version. Finally, we demonstrate that non-registration change detection can cause catastrophic damage to the state-of-the-art methods. Our code and dataset are available at https://github.com/ShanZard/NRCD.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 33 references that are in the map. First posted on arXiv 15 May 2025.
Builds on
13 of 33 references.
References · 13
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2020A Survey on Visual Transformercited by 653
- 2018Albumentations: fast and flexible image augmentationscited by 558
- 2020A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospectscited by 396
- 2021Remote Sensing Image Change Detection with Transformerscited by 305
- 2022A Transformer-Based Siamese Network for Change Detectioncited by 243
- 2023Adapting Segment Anything Model for Change Detection in HR Remote Sensing Imagescited by 56
- 2024Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagerycited by 30
- 2023HCGMNET: A Hierarchical Change Guiding Map Network For Change Detectioncited by 16
- 2025ROS-SAM: High-Quality Interactive Segmentation for Remote Sensing Moving Objectcited by 15
- 2022RDP-Net: Region Detail Preserving Network for Change Detectioncited by 13
- 2023Adjacent-Level Feature Cross-Fusion With 3-D CNN for Remote Sensing Image Change Detectioncited by 13
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Citing papers per year: 2026: 1.
1 paper.