# Open-CD: A Comprehensive Toolbox for Change Detection

arXiv: https://arxiv.org/abs/2407.15317 · HTML: https://mlsanity.com/paper/2407.15317/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 42 references that are in the map.
- First posted on arXiv 22 Jul 2024.

## Builds on (most cited first, 20 of 20)

- [SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers](https://mlsanity.com/paper/2105.15203/) (2021)
- [MMDetection: Open MMLab Detection Toolbox and Benchmark](https://mlsanity.com/paper/1906.07155/) (2019)
- [Fully Convolutional Siamese Networks for Change Detection](https://mlsanity.com/paper/1810.08462/) (2018)
- [Remote Sensing Image Change Detection with Transformers](https://mlsanity.com/paper/2103.00208/) (2021)
- [A Transformer-Based Siamese Network for Change Detection](https://mlsanity.com/paper/2201.01293/) (2022)
- [Changer: Feature Interaction is What You Need for Change Detection](https://mlsanity.com/paper/2209.08290/) (2022)
- [S2Looking: A Satellite Side-Looking Dataset for Building Change Detection](https://mlsanity.com/paper/2107.09244/) (2021)
- [MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining](https://mlsanity.com/paper/2403.13430/) (2024)
- [Change is Everywhere: Single-Temporal Supervised Object Change Detection in Remote Sensing Imagery](https://mlsanity.com/paper/2108.07002/) (2021)
- [A New Learning Paradigm for Foundation Model-based Remote Sensing Change Detection](https://mlsanity.com/paper/2312.01163/) (2023)
- [Changen2: Multi-Temporal Remote Sensing Generative Change Foundation Model](https://mlsanity.com/paper/2406.17998/) (2024)
- [TINYCD: A (Not So) Deep Learning Model For Change Detection](https://mlsanity.com/paper/2207.13159/) (2022)
- [Semantic Change Detection with Asymmetric Siamese Networks](https://mlsanity.com/paper/2010.05687/) (2020)
- [HANet: A Hierarchical Attention Network for Change Detection With Bitemporal Very-High-Resolution Remote Sensing Images](https://mlsanity.com/paper/2404.09178/) (2024)
- [Change Guiding Network: Incorporating Change Prior to Guide Change Detection in Remote Sensing Imagery](https://mlsanity.com/paper/2404.09179/) (2024)
- [Time Travelling Pixels: Bitemporal Features Integration with Foundation Model for Remote Sensing Image Change Detection](https://mlsanity.com/paper/2312.16202/) (2023)
- [Scalable Multi-Temporal Remote Sensing Change Data Generation via Simulating Stochastic Change Process](https://mlsanity.com/paper/2309.17031/) (2023)
- [Detecting Building Changes with Off-Nadir Aerial Images](https://mlsanity.com/paper/2301.10922/) (2023)
- [ChangeAnywhere: Sample Generation for Remote Sensing Change Detection via Semantic Latent Diffusion Model](https://mlsanity.com/paper/2404.08892/) (2024)
- [Single-Temporal Supervised Learning for Universal Remote Sensing Change Detection](https://mlsanity.com/paper/2406.15694/) (2024)

## Built on by (most cited first, 11 of 11)

- [DynamicEarth: How Far are We from Open-Vocabulary Change Detection?](https://mlsanity.com/paper/2501.12931/) (2025)
- [3DGS-CD: 3D Gaussian Splatting-based Change Detection for Physical Object Rearrangement](https://mlsanity.com/paper/2411.03706/) (2024)
- [JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework](https://mlsanity.com/paper/2502.13407/) (2025)
- [Beyond Quadratic: Linear-Time Change Detection with RWKV](https://mlsanity.com/paper/2603.19606/) (2026)
- [M2CD: A Unified MultiModal Framework for Optical-SAR Change Detection with Mixture of Experts and Self-Distillation](https://mlsanity.com/paper/2503.19406/) (2025)
- [Advancing Weakly-Supervised Change Detection in Satellite Images via Adversarial Class Prompting](https://mlsanity.com/paper/2508.17186/) (2025)
- [ChangeBridge: Spatiotemporal Image Generation with Multimodal Controls for Remote Sensing](https://mlsanity.com/paper/2507.04678/) (2025)
- [RS-MTDF: Multi-Teacher Distillation and Fusion for Remote Sensing Semi-Supervised Semantic Segmentation](https://mlsanity.com/paper/2506.08772/) (2025)
- [Compress-Align-Detect: onboard change detection from unregistered images](https://mlsanity.com/paper/2507.15578/) (2025)
- [UrbanCDNet: Appearance-Robust and Boundary-Aware Bitemporal Change Detection for Korean Urban Building Monitoring](https://mlsanity.com/paper/2606.29781/) (2026)
- [Fidelity-Diversity-Consistency (FDC): Data Pruning for Remote Sensing Change Detection](https://mlsanity.com/paper/2608.21754/) (2026)

## Abstract (arXiv)

We present Open-CD, a change detection toolbox that contains a rich set of change detection methods as well as related components and modules. The toolbox started from a series of open source general vision task tools, including OpenMMLab Toolkits, PyTorch Image Models, etc. It gradually evolves into a unified platform that covers many popular change detection methods and contemporary modules. It not only includes training and inference codes, but also provides some useful scripts for data analysis. We believe this toolbox is by far the most complete change detection toolbox. In this report, we introduce the various features, supported methods and applications of Open-CD. In addition, we also conduct a benchmarking study on different methods and components. We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new change detectors. Code and models are available at https://github.com/likyoo/open-cd. Pioneeringly, this report also includes brief descriptions of the algorithms supported in Open-CD, mainly contributed by their authors. We sincerely encourage researchers in this field to participate in this project and work together to create a more open community. This toolkit and report will be kept updated.