Active Learning Papers & Codes

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1. 2017-[CEAL]Cost-Effective Active Learning for Deep Image Classification
   [paper]
   [code] [keras]
   [code] [pytorch]

2. 2017-[CEAL]Cost-Effective Active Learning for Melanoma Segmentation
   [paper]
   [code] [keras] official
   [code] [keras] official

3. 2019-Sampling Bias in Deep Active Classification: An Empirical Study
   [paper]
   [code] [pytorch] official
   [code] [python package] official

4. 2018-modAL: A modular active learning framework for Python
   [paper]
   [code] [keras][python package]
   [doc]

5. 2020 ICCT-Variational Adversarial Active Learning
   [paper]
   [code] [pytorch] official
   [code] [pytorch] Sequential-GCN-for-Active-Learning
   [code] [pytorch] Visual-Transformer-for-Task-aware-Active-Learning

6. 2019-ALiPy: Active Learning in Python (A toolbox)
   [paper]
   [code] [python package]
   [doc]

7. 2021-Can Active Learning Preemptively Mitigate Fairness Issues?
   [paper]
   [code] [pytorch]
   [code] [python package]
   [doc]

Active Learning for Segmentation

1. 2017-[CEAL]Cost-Effective Active Learning for Melanoma Segmentation
   [paper]
   [code] [keras] official
   [code] [keras] official

2. 2020 CVPR-ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation
   [paper]
   [code] [pytorch]

3. 2019-Deep Active Learning for Axon-Myelin Segmentation on Histology Data
   [paper]
   [code] [keras] official
   [code] [keras]

4. 2020 ICLR-Reinforced active learning for image segmentation
   [paper]
   [code] [pytorch]

5. 2017 MICCAI-Suggestive Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation
   [paper]

6. 2012 CVPR-Active learning for semantic segmentation with expected change
   [paper]

7. 2011 MICCAI-Active Learning for Interactive 3D Image Segmentation
   [paper]

8. 2011 TGRS-Hyperspectral Image Segmentation Using a New Bayesian Approach With Active Learning
   [paper]