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Unsupervised Domain Adaptation Papers and Code

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Unsupervised Domain Adaptation

The resources only focus on unsupervised domain adapation(UDA) and these include related papers and the codes from top conferences and journals. You are welcome to pull any requests as you will. I'll sort out the content soon.

Conference Papers

2020 Conference Papers

| Abbreviation | Paper Title | Source Link | Code | Tags | | ------------ | ----------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | | MRNet | Unsupervised Scene Adaptation with Memory Regularization in vivo | IJCAI2019 | Pytorch(Official) |

Memory Regularization
|

2019 Conference Papers

| Abbreviation | Paper Title | Source Link | Code | Tags | | ------------ | ----------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | | MADAN | Multi-source Domain Adaptation for Semantic Segmentation | NeurIPS2019 | Pytorch(Official) |

CyCADA
Sub-Domain
| | CAG_UDA | Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation | NeurIPS2019 | Pytorch0.4(Official) |
Class-Aware
Pseudo-Labels
Warm-Up-Training
| | Wen's | Bayesian Uncertainty Matching for Unsupervised Domain Adaptation | IJCAI2019 | |
Label-Shift Adversarial
| | DADA | DADA: Depth-Aware Domain Adaptation in Semantic Segmentation | ICCV2019 | Pytorch1.2(Official) |
Adversarial
| | CAT | Cluster Alignment With a Teacher for Unsupervised Domain Adaptation | ICCV2019 | Tensorflow1.10(Official) |
Class-Conditional
Pseudo-Labels
| | MaxSquare | Domain Adaptation for Semantic Segmentation With Maximum Squares Loss | ICCV2019 | Pytorch1.0(Official) |
Class-Imbalance
Entropy-Minimization
Weight-Ratio
| | JD-BW | Batch Weight for Domain Adaptation With Mass Shift | ICCV2019 | |
Imbalance
Cycle-GANs
Importance-Sampling
| | Tsai's | Domain Adaptation for Structured Output via Discriminative Patch Representations | ICCV2019 | Project(Official) |
Cluster
Patch-Level
Adversarial Alignment
| | UM-Adapt | UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation | ICCV2019 | |
Contour-based-Content-Regularization
| | AFN | Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation | ICCV2019 | Pytorch0.4(Official) |
Feature-Norm
Norm-Discrepancy
Partial-DA
| |M3SDA | Moment Matching for Multi-Source Domain Adaptation | ICCV2019 | Pytorch0.3(Official) |
Moment-Matching
Multi-Source
| | Safa's| Unsupervised Domain Adaptation via Regularized Conditional Alignment | ICCV2019 | |
Conditional-Distribution
Adversarial-Regularization
| | DTA | Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation | ICCV2019 | Pytorch(Official) |
Cluster-Assumption
Adversarial-Dropout
KL
| | BSP | Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation | ICML2019 | Pytorch(Official) |
LDA-SVD->BSP
Between-class Within-class
| | DEV | Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation | ICML2019 | Sklearn(Official) |
Density-Ratio-Estimation
Variance-Reduction
| | Zhao's | On Learning Invariant Representation for Domain Adaptation | ICML2019 | Code(empty) |
Theory
Conditional-Shfit
Information-Theoretic-Lower-Bound
| | Wu's | Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment | ICML2019 | |
Theory
Label-Shift
Asymmetrically-Relaxed-Distances
| | MDD | Bridging Theory and Algorithm for Domain Adaptation | ICML2019 | Pytorch(Official) |
Theory
Margin-Disparity-Discrepancy
Rademacher-Complexity
| | CADA | Attending to Discriminative Certainty for Domain Adaptation | CVPR2019 arXiv | Code(Empty) |
Region-Adaptation
Bayesian-Framework
Attention
| | d-SNE | d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding | CVPR2019 Oral arXiv |MXNet-Gluon(Official)|
Hausdorff-Distance
Domain-Generalization
| | GCAN | GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation | CVPR2019 | |
Structureaware-Alignment
Domain-Alignment
Class-Centroid-Alignment
| | GIO-Ada | Learning Semantic Segmentation From Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach | CVPR2019 | |
Geometric-Information
Adversarial-Training
Depth-and-Semantic-Prediction
| | DISE | All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation | CVPR2019 | Pytorch(Official) |
Domain-Invariant-Structure
Domain-Specific-Representations
| | DSBN | Domain-Specific Batch Normalization for Unsupervised Domain Adaptation | CVPR2019 | |
Batch-Normalization
Pseudo-Labels
| | DWT | Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss | CVPR2019 | |
Min-Entropy Consensus loss
Domain-Alignment-Layer
| | BDL | Bidirectional Learning for Domain Adaptation of Semantic Segmentation | CVPR2019 | Pytorch(Official) |
Image-Translation
Alternative Learning
Perceptual-Loss
| | CAN | Contrastive Adaptation Network for Unsupervised Domain Adaptation | CVPR2019 | |
Intra-Class-Discrepancy
Inter-Class-Discrepancy
CDD-Metric
| | GPDA | Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach | CVPR2019 Oral | |
MCD->GP
Classifier’s-Posterior-Distribution
| | Tran's | Joint Pixel and Feature-level Domain Adaptation in the Wild | CVPR2019 | |
Combining-Many-Method
| | UAN | Universal Domain Adaptation | CVPR2019 | |
Sample-Level
Partial and Open Set
| | ADVENT | ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation | CVPR2019 Oral | Code(Empty) |
Meta-Sub-Target
| | AMEAN | Blending-Target Domain Adaptation by Adversarial Meta-Adaptation Networks | CVPR2019 Oral | Pytorch(Official) |
Multiple Sub-targets
Category-Misalignment
| | TPN | Transferrable Prototypical Networks for Unsupervised Domain Adaptation | CVPR2019 Oral | |
Non-linear-Mapping
Pseudo-Label
Score-Distribution
| | PFAN | Progressive Feature Alignment for Unsupervised Domain Adaptation | CVPR2019 | |
Intra-Class-Variation
Adaptive-Prototype-Alignment
Non-Saturated-Classifier
| | SymNets | Domain-Symmetric Networks for Adversarial Domain Adaptation | CVPR2019 | Pytorch(Official) |
Symmetric-Classifiers
Domain-Confusion
Category-Level
| | CLAN | Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation | CVPR2019 Oral | Pytorch(Official) |
Category-Level
Co-training
| | SWD | Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation | CVPR2019 | |
Wasserstein-Discrepancy
|

2018 Conference Papers

| Abbreviation | Paper Title | Source Link | Code | Tags | | ---------------- | ----------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------- | | Dhouib's | Revisiting -similarity learning for domain adaptation | NeurIPS2018 | |

Worst-Margin-Term
Theory
Similarity-Learning
| | CDAN | Conditional Adversarial Domain Adaptation | NeurIPS2018 | Code(Empty) |
Joint-Causal-Inference
Separating-Sets
| | Magliacane's | Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions | NeurIPS2018 | | | | Co-DA | Co-regularized Alignment for Unsupervised Domain Adaptation | NeurIPS2018 | |
Class-Conditional
Diverse-Feature-Embeddings
Co-regularize-Alignments
| | JDDA | Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation | AAAI2019 | Tensorflow(Official) |
Domain-Shift
Instance-Based-Loss
Center-Based-Loss
| | PADA | Partial Adversarial Domain Adaptation | ECCV2018 | Pytorch(Official) | | | GAKT | Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation | ECCV2018 | | | | Kang's | Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization | ECCV2018 | | | | MEDA | Visual Domain Adaptation with Manifold Embedded Distribution Alignment | ACM MM2018 | Matlab(Official) | | | CyCADA | Cycle Consistent Adversarial Domain Adaptation | ICML2018 | Pytorch(Official) | | | MSTN | Learning Semantic Representations for Unsupervised Domain Adaptation | ICML2018 | Tensorflow(Official) | | | DeppJDOT | DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain Adaptation | arXiv2018 ECCV2018 | | | Saito's | Open Set Domain Adaptation by Backpropagation | arXiv2018 ECCV2018 | TensorFlow Pytorch | | | I2IAdapt | Image to Image Translation for Domain Adaptation | CVPR2018 | | | | PDA | Importance Weighted Adversarial Nets for Partial Domain Adaptation | CVPR2018 | | | | MCD_DA | Maximum Classifier Discrepancy for Unsupervised Domain Adaptation | CVPR2018 | Pytorch(Official) | | | RPTDA | Residual Parameter Transfer for Deep Domain Adaptation | CVPR2018 | | | | DIFA | Adversarial Feature Augmentation for Unsupervised Domain Adaptation | CVPR2018 | TensorFlow 1.3(Official) | | | SAN | Partial Transfer Learning with Selective Adversarial Networks | CVPR2018 | | | | DupGAN | Duplex Generative Adversarial Network for Unsupervised Domain Adaptation | CVPR2018 | Pytorch 0.1(Official) | | | GTA | Generate To Adapt: Aligning Domains using Generative Adversarial Networks | CVPR2018 | Pytorch(Official) | | | SimNet | Unsupervised Domain Adaptation with Similarity Learning | CVPR2018 | | | | KWC,KOT | Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation | CVPR2018 | | | | DCTN | Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift | CVPR2018 | | | | iCAN | Collaborative and Adversarial Network for Unsupervised Domain Adaptation | CVPR2018 | | | | RAAN | Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation | CVPR2018 | | | | MADA | Multi-Adversarial Domain Adaptation | AAAI2018 | Caffe(Official) | | | WDGRL | Wasserstein Distance Guided Representation Learning for Domain Adaptation | AAAI2018 | Tensorflow 1.3.0(Official) Pytorch | | | DIRT-T | A DIRT-T Approach to Unsupervised Domain Adaptation | ICLR2018 | Tensorflow(Official) | | | MT | Self-ensembling for Visual Domain Adaptation | ICLR2018 | Pytorch(Official) | | | CCN | Learning to Cluster in Order to Transfer Across Domains and Tasks | ICLR2018 | | | | MECA | Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation | ICLR2018 | Tensorflow(Official) | |

Conference Papers befor 2018

| Abbreviation | Paper Title | Source Link | Code | Tags | | ---------------------- | ------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---- | | ATI | Open Set Domain Adaptation | ICCV2017 | Matlab(Official) | | | AutoDIAL | Automatic DomaIn Alignment Layers | ICCV2017 | Caffe(Official) | | | DAassoc | Associative Domain Adaptation | ICCV2017 | Tensorflow(Official) | | | TAISL | When Unsupervised Domain Adaptation Meets Tensor Representations | ICCV2017 | Matlab(Official) | | | CCSA | Unified Deep Supervised Domain Adaptation and Generalization | ICCV2017 | Keras(Official) | | | UNIT | Unsupervised Image-to-Image Translation Networks | NIPS2017 | Pytorch(Official) | | | Luo's | Label Efficient Learning of Transferable Representations acrosss Domains and Tasks | NIPS2017 | Project | | | JDOT | Joint Distribution Optimal Transportation for Domain Adaptation | NIPS2017 | Python(Official) | | | FADA | Few-Shot Adversarial Domain Adaptation | NIPS2017 | Pytorch | | | ADDA | Adversarial Discriminative Domain Adaptation | CVPR2017 | Tensorflow(Official) Pytorch [Pytorch] | | | PixelDA | Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks | CVPR2017 | Tensorflow(Official) [Pytorch] | | | JGSA | Joint Geometrical and Statistical Alignment for Visual Domain Adaptation | CVPR2017 | Matlab(Official) | | | ILS | Learning an Invariant Hilbert Space for Domain Adaptation | CVPR2017 | Matlab(Official) | | | DAH | Deep Hashing Network for Unsupervised Domain Adaptation | CVPR2017 | Matlab(Official) | | | Wu's | A Compact DNN: Approaching GoogLeNet-Level Accuracy of Classification and Domain Adaptation | CVPR2017 | | | | WDAN | Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation | CVPR2017 | Caffe(Official) | | | JAN | Deep Transfer Learning with Joint Adaptation Networks | ICML2017 | Pytorch 0.2.0_3(Official) | | | ATDA | Asymmetric Tri-training for Unsupervised Domain Adaptation | ICML2017 | Tensorflow(Official) Tensorflow Pytorch | | | AdaBN | Revisiting Batch Normalization For Practical Domain Adaptation | ICLR2017 PR2018 | MXNet | | | DSN | Domain Separation Networks | NIPS2016 | Tensorflow(Official) Pytorch | | | Sener's | Learning Transferrable Representations for Unsupervised Domain Adaptation | NIPS2016 | | | | RTN | Unsupervised Domain Adaptation with Residual Transfer Networks | NIPS2016 | Code(Official) | | | DRCN | Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation | ECCV2016 | Tensorflow 1.0.1(Official) Pytorch | | | Deep CORAL | Deep CORAL: Correlation Alignment for Deep Domain Adaptation | ECCV2016 | C(Official) Pytorch 0.2 | | | RevGrad | Unsupervised Domain Adaptation by Backpropagation | ICML2015 | Caffe(Official) Tensorflow Pytorch | |

Journal Papers

| Abbreviation | Paper Title | Source Link | Code | Tags | | ------------------------- | ------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------- | | GDM | Adaptation Based on Generalized Discrepancy | JMLR2020 | |

Stability
Rademacher
Y-Discrepancy
| | TIT | Transfer Independently Together: A Generalized Framework for Domain Adaptation | TCyb2019 | |
Heterogeneous
Landmark-Selection
Multiple-Transformations
| | CV-CMD | Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment | InforSci2019 | Keras(Official) |
Domain-Specific-Activation-Distributions
Regularization
Probability-Metric
| | DICE | Aggregating Randomized Clustering-Promoting Invariant Projections for Domain Adaptation | TPAMI2019 | |
Intra-Domain-Structure
Multiple-Projections
Vote
| | DST-ELM | Domain Space Transfer Extreme Learning Machine for Domain Adaptation | TCyb2019 | |
Reconstruction
Domain-Structural-Knowledge
| | GsDsDL | Learning Domain-shared Group-sparse Representation for Unsupervised Domain Adaptation | PR2018 | | | | AdaBN | Revisiting Batch Normalization For Practical Domain Adaptation | ICLR2017 PR2018 | | | | LDADA | An Embarrassingly Simple Approach to Visual Domain Adaptation | TIP2018 | Matlab(Official) | | | DICD | Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation | TIP2018 | | | | HDANA | Heterogeneous Domain Adaptation Network Based on Autoencoder | JPDC2018 | | | | DKTL | Domain Class Consistency Based Transfer Learning For Image Classification Across Domains | InforSci2017 | | | | Ding's | Deep Domain Generalization With Structured Low-Rank Constraint | TIP2017 | | | | Venkateswara's survey | Deep-Learning Systems for Domain Adaptation in Computer Vision: Learning Transferable Feature Representations | SP Magazine | | | | BSWDA | Beyond Sharing Weights for Deep Domain Adaptation | TPAMI2016 | | | | SCA | Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization | TPAMI2016 | | | | DME | Distribution-Matching Embedding for Visual Domain Adaptation | JMLR2016 | | | | DANN | Domain-Adversarial Training of Neural Networks | JMLR2016 | Tensorflow(Official) Pytorch Pytorch | | | LSCDA | Unsupervised Domain Adaptation With Label and Structural Consistency | TIP2016 | | | | FLDA | Feature-Level Domain Adaptation | JMLR2016 | Matlab(Official) Python(Official) | |

arXiv Papers

| Abbreviation | Paper Title | Source Link | Code | Tags | | ----------------- | ------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------- | -------------------------------------------------------------------- | | MRNet+Rectify| Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation | arXiv 8 Mar 2020 | Pytorch(Official) |

Rectify Pseudo Label
,
Uncertainty
| | LPJT | Locality Preserving Joint Transfer for Domain Adaptation | arXiv 18 Jun 2019 | Matlab(Official) |
Feature && Sample
MMD
Re-weight
| | SDA-TCL | Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation | arXiv 10 Jun 2019 | |
Center-Loss
Pseudo-Label
| | SALT | SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation | arXiv 11 Jun 2019 | |
Meta-Auxiliary-Learning
Data-Geometries
Subspace-Alignment
| | Wang's | Discriminative Clustering for Robust Unsupervised Domain Adaptation | arXiv 30 May 2019 | |
Cluster-Dissimilarity
Adversarial-Learning
Label-Distributions
| | RADA | Adversarial Domain Adaptation Being Aware of Class Relationships | arXiv 28 May 2019 | |
Inter-Class-Semantic-Relationships
| | SRDA | Learning Smooth Representation for Unsupervised Domain Adaptation | arXiv 26 May 2019 | |
Decision-Boundary-and-Features
Local-Smooth-Discrepancy
| | Cicek's | Unsupervised Domain Adaptation via Regularized Conditional Alignment | arXiv 26 May 2019 | |
Class-Conditional
SSL-Regularization
Consistency-Loss
| | Wilson's | A Survey of Unsupervised Deep Domain Adaptation | arXiv 29 Mar 2019 | |
Survey
| | Zhang's | Transfer Adaptation Learning: A Decade Survey | arXiv 12 Mar 2019 | |
Survey
| | Kouw's | A Review of Single-source Unsupervised Domain Adaptation | arXiv 16 Jan 2019 | |
Review
| | Kouw's | An Introduction to Domain Adaptation and Transfer Learning | arXiv 31 Dec 2018 | |
Review
| | Le's | Theoretical Perspective of Deep Domain Adaptation | arXiv 15 Nov 2018 | |
Wasserstein Metric
| | Wang's survey | Deep visual domain adaptation: A survey | arXiv2018 NeCo2018 | |
Survey
| | IDDA | Looking back at Labels: A Class based Domain Adaptation Technique | IJCNN Poster | Project(Official) | | | IAFN | Unsupervised Domain Adaptation: An Adaptive Feature Norm Approach | arXiv 19 Nov | Pytorch(Official) | | | GDAN | Causal Generative Domain Adaptation Networks | arXiv 28 Jun 2018 | | | | M-ADDA | M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning | arXiv 6 Jul 2018 | Pytorch(Official) | | | DiDA | DiDA: Disentangled Synthesis for Domain Adaptation | arXiv 21 Mar 2018 | Pytorch(Official) | | | CMD | Robust Unsupervised Domain Adaptation for Neural Networks via Moment Alignment | arXiv 28 Mar 2018 | Keras(Official) | | | CDAAE | Cross-Domain Adversarial Auto-Encoder | arXiv 17 Apr 2018 | Tensorflow(Official) | |

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