Semi-supervised Change Detection
5 papers with code • 8 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Semi-supervised Change Detection
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GVLM
Most implemented papers
BLDNet: A Semi-supervised Change Detection Building Damage Framework using Graph Convolutional Networks and Urban Domain Knowledge
awadailab/gcn-remote-sensing
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While convolutional neural networks are at the core of recent change detection solutions, we present in this work, BLDNet, a novel graph formulation for building damage change detection and enable learning relationships and representations from both local patterns and non-stationary neighborhoods.
Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images
wgcban/SemiCD
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The performance of existing deep supervised CD methods is attributed to the large amounts of annotated data used to train the networks.
Semi-supervised Change Detection of Small Water Bodies Using RGB and Multispectral Images in Peruvian Rainforests
Artisanal and Small-scale Gold Mining (ASGM) is an important source of income for many households, but it can have large social and environmental effects, especially in rainforests of developing countries.
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation
LiheYoung/UniMatch
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CVPR 2023
In this work, we revisit the weak-to-strong consistency framework, popularized by FixMatch from semi-supervised classification, where the prediction of a weakly perturbed image serves as supervision for its strongly perturbed version.
C2F-SemiCD: A Coarse-to-Fine Semi-Supervised Change Detection Method Based on Consistency Regularization in High-Resolution Remote Sensing Images
chengxihan/c2f-semicd-and-c2f-cdnet
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A high-precision feature extraction model is crucial for change detection (CD).
