Awesome Segmentation Domain Adaptation

If you notice any result or the public code that has not been included in this page, please connect Zhedong Zheng without hesitation to add the method. You are welcomed! or create pull request.

Priorities are given to papers whose codes are published.


  • Cross-Region Domain Adaptation for Class-level Alignment [14 Sep 2021]
  • Contrastive Learning and Self-Training for Unsupervised Domain Adaptation in Semantic Segmentation [5 May 2021]
  • ACDC: The Adverse Conditions Dataset with Correspondences for Semantic Driving Scene Understanding [29 April 2021]
  • Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation [28 Apr 2021]
  • Class-Conditional Domain Adaptation on Semantic Segmentation [27 Nov 2019]
  • Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation [23 Oct 2019]
  • Restyling Data: Application to Unsupervised Domain Adaptation [24 Sep 2019]
  • Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation [2 Sep 2019]
  • FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation [8 Dec 2016]


  • Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation [TIP 2022][code]
  • Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation [IJCV 2021]
  • Affinity Space Adaptation for Semantic Segmentation Across Domains [TIP2020]
  • Semantic-aware short path adversarial training for cross-domain semantic segmentation [Neurocomputing 2019]
  • Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes [TIP 2019]


  • PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation [ACM MM2023] [Code]
  • DAformer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation [[CVPR2022]]
  • Class-balanced pixel-level self-labeling for domain adaptive semantic segmentation [[CVPR2022]]
  • Undoing the damage of label shift for cross-domain semantic segmentation [[CVPR2022]]
  • Adas: A direct adaptation strategy for multi-target domain adaptive semantic segmentation [[CVPR2022]]
  • Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation [ICCV2021]
  • Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation [CVPR2021]
  • Improving Domain Generalization in Urban-Scene Segmentationvia Instance Selective Whitening [CVPR2021]
  • Rethinking Ensemble-Distillation for Semantic Segmentation Based Unsupervised Domain Adaptation [CVPRW 2021]
  • Instance Adaptive Self-Training for Unsupervised Domain Adaptation [ECCV 2020]
  • Two-phase Pseudo Label Densification for Self-training based Domain Adaptation [ECCV 2020]
  • Unsupervised Scene Adaptation with Memory Regularization in vivo [IJCAI 2020] [code]
  • Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation [NeurIPS 2020][Pytorch]
  • Content-Consistent Matching for Domain Adaptive Semantic Segmentation [ECCV 2020] [Code]
  • Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation [CVPR 2020] [Code]
  • Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation[ECCV 2020]
  • An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation [AAAI2020]
  • Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation [NeurIPS2019]) [code]
  • MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling [WACV2020]
  • Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation [ICCV2019]
  • Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach [ICCV2019] [Pytorch]
  • SSF-DAN: Separated Semantic Feature Based Domain Adaptation Network for Semantic Segmentation [ICCV2019]
  • Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation [ICCV2019]
  • Domain Adaptation for Semantic Segmentation with Maximum Squares Loss [ICCV2019] [Pytorch]
  • Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation [ICCV2019]
  • DADA: Depth-aware Domain Adaptation in Semantic Segmentation [ICCV2019] [code]
  • Domain Adaptation for Structured Output via Discriminative Patch Representations [ICCV2019 Oral] [Project]
  • Not All Areas Are Equal: Transfer Learning for Semantic Segmentation via Hierarchical Region Selection [CVPR2019(Oral)(PDF Coming Soon)]
  • CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency [CVPR2019] [Project]
  • Bidirectional Learning for Domain Adaptation of Semantic Segmentation [CVPR2019] [Pytorch]
  • Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach [CVPR2019]
  • All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation [CVPR2019] [Pytorch]
  • DLOW: Domain Flow for Adaptation and Generalization [CVPR2019 Oral]
  • Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation [CVPR2019 Oral] [Pytorch]
  • ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation [CVPR2019 Oral] [Pytorch]
  • SPIGAN: Privileged Adversarial Learning from Simulation [ICLR2019]
  • Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation [ECCV2018]
  • Domain transfer through deep activation matching [ECCV2018]
  • Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training [ECCV2018]
  • DCAN: Dual channel-wise alignment networks for unsupervised scene adaptation [ECCV2018]
  • Fully convolutional adaptation networks for semantic segmentation [CVPR2018]
  • Learning to Adapt Structured Output Space for Semantic Segmentation [CVPR2018] [Pytorch]
  • Conditional Generative Adversarial Network for Structured Domain Adaptation [CVPR2018]
  • Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation [CVPR2018]
  • Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes [ICCV2017] [Journal Version]
  • No more discrimina- tion: Cross city adaptation of road scene segmenters [ICCV2017]