awesome-domain-adaptation

Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey

A Survey on Deep Domain Adaptation for LiDAR Perception

A Comprehensive Survey on Transfer Learning

Transfer Adaptation Learning: A Decade Survey

A review of single-source unsupervised domain adaptation

An introduction to domain adaptation and transfer learning

A Survey of Unsupervised Deep Domain Adaptation

Transfer Learning for Cross-Dataset Recognition: A Survey

Domain Adaptation for Visual Applications: A Comprehensive Survey

Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated Driving

A Review of Single-Source Deep Unsupervised Visual Domain Adaptation

Deep Visual Domain Adaptation: A Survey

A Survey on Deep Transfer Learning

Visual domain adaptation: A survey of recent advances

A Theory of Label Propagation for Subpopulation Shift

A General Upper Bound for Unsupervised Domain Adaptation

On Deep Domain Adaptation: Some Theoretical Understandings

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift

Bridging Theory and Algorithm for Domain Adaptation

On Learning Invariant Representation for Domain Adaptation

Unsupervised Domain Adaptation Based on Source-guided Discrepancy

Learning Bounds for Domain Adaptation

Analysis of Representations for Domain Adaptation

On a Regularization of Unsupervised Domain Adaptation in RKHS

Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice

On generalization in moment-based domain adaptation

A theory of learning from different domains

Visualizing Adapted Knowledge in Domain Transfer

SPA: A Graph Spectral Alignment Perspective for Domain Adaptation

Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation

A Closer Look at Smoothness in Domain Adversarial Training

ToAlign: Task-oriented Alignment for Unsupervised Domain Adaptation

Adversarial Unsupervised Domain Adaptation With Conditional and Label Shift: Infer, Align and Iterate

Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation

Re-energizing Domain Discriminator with Sample Relabeling for Adversarial Domain Adaptation

Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation

MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation

Self-adaptive Re-weighted Adversarial Domain Adaptation

DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer

SSA-DA: Bi-dimensional feature alignment for cross-domain object detection

Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation

MCAR: Adaptive object detection with dual multi-label prediction

Gradually Vanishing Bridge for Adversarial Domain Adaptation

Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation

Adversarial-Learned Loss for Domain Adaptation

Structure-Aware Feature Fusion for Unsupervised Domain Adaptation

Adversarial Domain Adaptation with Domain Mixup

Discriminative Adversarial Domain Adaptation

Bi-Directional Generation for Unsupervised Domain Adaptation

Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning

Curriculum based Dropout Discriminator for Domain Adaptation

Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition

Transfer Learning with Dynamic Adversarial Adaptation Network

Joint Adversarial Domain Adaptation

Cycle-consistent Conditional Adversarial Transfer Networks

Learning Disentangled Semantic Representation for Domain Adaptation

Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation

Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers

Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation

Cluster Alignment with a Teacher for Unsupervised Domain Adaptation

Unsupervised Domain Adaptation via Regularized Conditional Alignment

Attending to Discriminative Certainty for Domain Adaptation

GCAN: Graph Convolutional Adversarial Network for Unsupervised Domain Adaptation

Domain-Symmetric Networks for Adversarial Domain Adaptation

DLOW: Domain Flow for Adaptation and Generalization

Progressive Feature Alignment for Unsupervised Domain Adaptation

Gotta Adapt ’Em All: Joint Pixel and Feature-Level Domain Adaptation for Recognition in the Wild

Looking back at Labels: A Class based Domain Adaptation Technique

Consensus Adversarial Domain Adaptation

Transferable Attention for Domain Adaptation

Exploiting Local Feature Patterns for Unsupervised Domain Adaptation

Augmented Cyclic Adversarial Learning for Low Resource Domain Adaptation

Conditional Adversarial Domain Adaptation

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

Deep Adversarial Attention Alignment for Unsupervised Domain Adaptation: the Benefit of Target Expectation Maximization

Learning Semantic Representations for Unsupervised Domain Adaptation

CyCADA: Cycle-Consistent Adversarial Domain Adaptation

From source to target and back: Symmetric Bi-Directional Adaptive GAN

Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation

Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

Adversarial Feature Augmentation for Unsupervised Domain Adaptation

Duplex Generative Adversarial Network for Unsupervised Domain Adaptation

Generate To Adapt: Aligning Domains using Generative Adversarial Networks

Image to Image Translation for Domain Adaptation

Unsupervised Domain Adaptation with Similarity Learning

Conditional Generative Adversarial Network for Structured Domain Adaptation

Collaborative and Adversarial Network for Unsupervised Domain Adaptation

Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation

Multi-Adversarial Domain Adaptation

Wasserstein Distance Guided Representation Learning for Domain Adaptation

Incremental Adversarial Domain Adaptation for Continually Changing Environments

Adversarial Dropout Regularization

A DIRT-T Approach to Unsupervised Domain Adaptation

Label Efficient Learning of Transferable Representations acrosss Domains and Tasks

Adversarial Discriminative Domain Adaptation

Unsupervised Pixel–Level Domain Adaptation with Generative Adversarial Networks

Domain Separation Networks

Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation

Domain-Adversarial Training of Neural Networks

Unsupervised Domain Adaptation by Backpropagation

Incremental Unsupervised Domain-Adversarial Training of Neural Networks

Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice

Adversarial Learning and Interpolation Consistency for Unsupervised Domain Adaptation

TarGAN: Generating target data with class labels for unsupervised domain adaptation

Bi-Directional Generation for Unsupervised Domain Adaptation

Enlarging Discriminative Power by Adding an Extra Class in Unsupervised Domain Adaptation

Learning Domain Adaptive Features with Unlabeled Domain Bridges

Reducing Domain Gap via Style-Agnostic Networks

Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment

Adversarial Variational Domain Adaptation

Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation

SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation

Joint Semantic Domain Alignment and Target Classifier Learning for Unsupervised Domain Adaptation

Adversarial Domain Adaptation Being Aware of Class Relationships

Domain-Invariant Adversarial Learning for Unsupervised Domain Adaption

Unsupervised Domain Adaptation using Deep Networks with Cross-Grafted Stacks

DART: Domain-Adversarial Residual-Transfer Networks for Unsupervised Cross-Domain Image Classification

Unsupervised Domain Adaptation using Generative Models and Self-ensembling

Domain Confusion with Self Ensembling for Unsupervised Adaptation

Improving Adversarial Discriminative Domain Adaptation

M-ADDA: Unsupervised Domain Adaptation with Deep Metric Learning

Factorized Adversarial Networks for Unsupervised Domain Adaptation

DiDA: Disentangled Synthesis for Domain Adaptation

Unsupervised Domain Adaptation with Adversarial Residual Transform Networks

Causal Generative Domain Adaptation Networks

Transferable Representation Learning with Deep Adaptation Networks

Robust unsupervised domain adaptation for neural networks via moment alignment

Domain Conditioned Adaptation Network

HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation

Normalized Wasserstein for Mixture Distributions With Applications in Adversarial Learning and Domain Adaptation

Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation

Residual Parameter Transfer for Deep Domain Adaptation

Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation

Central Moment Discrepancy for Unsupervised Domain Adaptation , ,

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

Learning Transferable Features with Deep Adaptation Networks

Unsupervised Domain Adaptation with Residual Transfer Networks

Deep Transfer Learning with Joint Adaptation Networks

Deep Domain Confusion: Maximizing for Domain Invariance

Hypothesis Disparity Regularized Mutual Information Maximization

Global-Local Regularization Via Distributional Robustness

MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning

LAMDA: Label Matching Deep Domain Adaptation

TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport

Unbalanced minibatch Optimal Transport; applications to Domain Adaptation

Graph Optimal Transport for Cross-Domain Alignment

Margin-aware Adversarial Domain Adaptation with Optimal Transport

Metric Learning in Optimal Transport for Domain Adaptation

Reliable Weighted Optimal Transport for Unsupervised Domain Adaptation

Enhanced Transport Distance for Unsupervised Domain Adaptation

Differentially Private Optimal Transport: Application to Domain Adaptation

DeepJDOT: Deep Joint distribution optimal transport for unsupervised domain adaptation

Joint Distribution Optimal Transportation for Domain Adaptation

CDOT: Continuous Domain Adaptation using Optimal Transport

Incremental Unsupervised Domain-Adversarial Training of Neural Networks

Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation

Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners

Cycle Self-Training for Domain Adaptation

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

Instance Adaptive Self-Training for Unsupervised Domain Adaptation

Self-training Avoids Using Spurious Features Under Domain Shift

Two-phase Pseudo Label Densification for Self-training based Domain Adaptation

Probabilistic Contrastive Learning for Domain Adaptation

Gradual Domain Adaptation via Self-Training of Auxiliary Models

Self-Supervised CycleGAN for Object-Preserving Image-to-Image Domain Adaptation

Unsupervised Domain Adaptation through Self-Supervision

Safe Self-Refinement for Transformer-Based Domain Adaptation [

Prior Knowledge Guided Unsupervised Domain Adaptation

Revisiting Unsupervised Domain Adaptation Models: a Smoothness Perspective

Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment

Pareto Domain Adaptation

ToAlign: Task-Oriented Alignment for Unsupervised Domain Adaptation

A Prototype-Oriented Framework for Unsupervised Domain Adaptation

Understanding the Limits of Unsupervised Domain Adaptation via Data Poisoning

SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation

Transporting Causal Mechanisms for Unsupervised Domain Adaptation

Semantic Concentration for Domain Adaptation

FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation

Domain Adaptation With Auxiliary Target Domain-Oriented Classifier

Conditional Bures Metric for Domain Adaptation

DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation

Visualizing Adapted Knowledge in Domain Transfer

Instance Level Affinity-Based Transfer for Unsupervised Domain Adaptation

Dynamic Domain Adaptation for Efficient Inference

Transferable Semantic Augmentation for Domain Adaptation

MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation

DRANet: Disentangling Representation and Adaptation Networks for Unsupervised Cross-Domain Adaptation

Dynamic Weighted Learning for Unsupervised Domain Adaptation

Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift

Transferable Calibration with Lower Bias and Variance in Domain Adaptation

A Dictionary Approach to Domain-Invariant Learning in Deep Networks

Heuristic Domain Adaptation

Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search

Mind the Discriminability: Asymmetric Adversarial Domain Adaptation

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation

CSCL: Critical Semantic-Consistent Learning for Unsupervised Domain Adaptation

Minimum Class Confusion for Versatile Domain Adaptation

Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift

Label Propagation with Augmented Anchors: A Simple Semi-Supervised Learning baseline for Unsupervised Domain Adaptation

Unsupervised Domain Adaptation via Structurally Regularized Deep Clustering

Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

Unsupervised Domain Adaptation With Hierarchical Gradient Synchronization

Spherical Space Domain Adaptation With Robust Pseudo-Label Loss

Stochastic Classifiers for Unsupervised Domain Adaptation

Structure Preserving Generative Cross-Domain Learning

Light-weight Calibrator: A Separable Component for Unsupervised Domain Adaptation

Domain Adaptive Multiflow Networks

Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment

Visual Domain Adaptation by Consensus-based Transfer to Intermediate Domain

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

CUDA: Contradistinguisher for Unsupervised Domain Adaptation

Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment

Batch Weight for Domain Adaptation With Mass Shift

Switchable Whitening for Deep Representation Learning

Confidence Regularized Self-Training

Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation

Transferrable Prototypical Networks for Unsupervised Domain Adaptation

Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

Unsupervised Domain Adaptation using Feature-Whitening and Consensus Loss

Domain Specific Batch Normalization for Unsupervised Domain Adaptation

AdaGraph: Unifying Predictive and Continuous Domain Adaptation through Graphs

Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach

Contrastive Adaptation Network for Unsupervised Domain Adaptation

Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation

Unsupervised Domain Adaptation via Calibrating Uncertainties

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation

Unsupervised Domain Adaptation for Distance Metric Learning

Co-regularized Alignment for Unsupervised Domain Adaptation

Domain Invariant and Class Discriminative Feature Learning for Visual Domain Adaptation

Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation

Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation

Unsupervised Domain Adaptation with Distribution Matching Machines

Learning to cluster in order to transfer across domains and tasks

Self-Ensembling for Visual Domain Adaptation

Minimal-Entropy Correlation Alignment for Unsupervised Deep Domain Adaptation

Associative Domain Adaptation

AutoDIAL: Automatic DomaIn Alignment Layers

Asymmetric Tri-training for Unsupervised Domain Adaptation

Learning Transferrable Representations for Unsupervised Domain Adaptation

Target-Independent Domain Adaptation for WBC Classification using Generative Latent Search

Adaptive Batch Normalization for practical domain adaptation

Unsupervised Domain Adaptation by Mapped Correlation Alignment

Low-confidence Samples Matter for Domain Adaptation

Improving Unsupervised Domain Adaptation with Variational Information Bottleneck

Deep causal representation learning for unsupervised domain adaptation

Domain-invariant Learning using Adaptive Filter Decomposition

Discriminative Clustering for Robust Unsupervised Domain Adaptation

Virtual Mixup Training for Unsupervised Domain Adaptation

Learning Smooth Representation for Unsupervised Domain Adaptation

Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation

Easy Transfer Learning By Exploiting Intra-domain Structures

Domain Discrepancy Measure Using Complex Models in Unsupervised Domain Adaptation

Domain Alignment with Triplets

Deep Discriminative Learning for Unsupervised Domain Adaptation

POUF: Prompt-oriented unsupervised fine-tuning for large pre-trained models

Semi-Supervised Domain Adaptation With Source Label Adaptation

Multi-level Consistency Learning for Semi-supervised Domain Adaptation

AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation

CLDA: Contrastive Learning for Semi-Supervised Domain Adaptation

Deep Co-Training With Task Decomposition for Semi-Supervised Domain Adaptation

ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation

Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation

Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation

Learning Invariant Representations and Risks for Semi-supervised Domain Adaptation

Improving Semi-Supervised Domain Adaptation Using Effective Target Selection and Semantics

Attract, Perturb, and Explore: Learning a Feature Alignment Network for Semi-supervised Domain Adaptation

Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation

Bidirectional Adversarial Training for Semi-Supervised Domain Adaptation

Semi-supervised Domain Adaptation via Minimax Entropy

Context-guided entropy minimization for semi-supervised domain adaptation

Pred&Guide: Labeled Target Class Prediction for Guiding Semi-Supervised Domain Adaptation

MiCo: Mixup Co-Training for Semi-Supervised Domain Adaptation

Opposite Structure Learning for Semi-supervised Domain Adaptation

Reducing Domain Gap via Style-Agnostic Networks

Towards Accurate and Robust Domain Adaptation under Noisy Environments

Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration

Transferable Curriculum for Weakly-Supervised Domain Adaptation

Butterfly: Robust One-step Approach towards Wildly-unsupervised Domain Adaptation

Collaborative Learning With Disentangled Features for Zero-Shot Domain Adaptation

Zero-Shot Day-Night Domain Adaptation with a Physics Prior

High Resolution Zero-Shot Domain Adaptation of Synthetically Rendered Face Images

Adversarial Learning for Zero-shot Domain Adaptation

HGNet: Hybrid Generative Network for Zero-shot Domain Adaptation

Zero-shot Domain Adaptation Based on Attribute Information

Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation

Generalized Zero-Shot Learning with Deep Calibration Network

Zero-Shot Deep Domain Adaptation

Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation

One-Shot Adaptation of Supervised Deep Convolutional Models

One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning

Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation

Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels

Domain-Adaptive Few-Shot Learning

Few-shot Domain Adaptation by Causal Mechanism Transfer

Few-Shot Adaptive Faster R-CNN

d-SNE: Domain Adaptation using Stochastic Neighborhood Embedding

Few-Shot Adversarial Domain Adaptation

Feature transformation ensemble model with batch spectral regularization for cross-domain few-shot classification

Ensemble model with batch spectral regularization and data blending for cross-domain few-shot learning with unlabeled data

Implicit Semantic Response Alignment for Partial Domain Adaptation

Adversarial Reweighting for Partial Domain Adaptation

A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation

Discriminative Partial Domain Adversarial Network

Selective Transfer With Reinforced Transfer Network for Partial Domain Adaptation

Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation

Multi-Weight Partial Domain Adaptation

Learning to Transfer Examples for Partial Domain Adaptation

Partial Adversarial Domain Adaptation

Importance Weighted Adversarial Nets for Partial Domain Adaptation

Partial Transfer Learning with Selective Adversarial Networks

Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice

Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation

Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice

Tackling Partial Domain Adaptation with Self-Supervision

Domain Adversarial Reinforcement Learning for Partial Domain Adaptation

Towards Novel Target Discovery Through Open-Set Domain Adaptation

On the Effectiveness of Image Rotation for Open Set Domain Adaptation

Multi-Source Open-Set Deep Adversarial Domain Adaptation

Progressive Graph Learning for Open-Set Domain Adaptation

Joint Partial Optimal Transport for Open Set Domain Adaptation

Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation

Towards Inheritable Models for Open-Set Domain Adaptation

Attract or Distract: Exploit the Margin of Open Set

Separate to Adapt: Open Set Domain Adaptation via Progressive Separation

Weakly Supervised Open-set Domain Adaptation by Dual-domain Collaboration

Learning Factorized Representations for Open-set Domain Adaptation

Open Set Domain Adaptation by Backpropagation

Open Set Domain Adaptation

Open-set domain adaptation by deconfounding domain gaps

Unsupervised Multi-Class Domain Adaptation: Theory, Algorithms, and Practice

Adversarial Network with Multiple Classifiers for Open Set Domain Adaptation

Collaborative Training of Balanced Random Forests for Open Set Domain Adaptation

Known-class Aware Self-ensemble for Open Set Domain Adaptation

Universal Domain Adaptation for Robust Handling of Distributional Shifts in NLP

Subsidiary Prototype Alignment for Universal Domain Adaptation

OVANet: One-vs-All Network for Universal Domain Adaptation

Active Universal Domain Adaptation

Domain Consensus Clustering for Universal Domain Adaptation

Divergence Optimization for Noisy Universal Domain Adaptation

Universal Domain Adaptation through Self Supervision

Learning to Detect Open Classes for Universal Domain Adaptation

Universal Source-Free Domain Adaptation

Universal Domain Adaptation

Universal Model Adaptation by Style Augmented Open-set Consistency

Universal Multi-Source Domain Adaptation

A Sample Selection Approach for Universal Domain Adaptation

Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation

Open Compound Domain Adaptation

Source-Free Open Compound Domain Adaptation in Semantic Segmentation

Confident Anchor-Induced Multi-Source Free Domain Adaptation

mDALU: Multi-Source Domain Adaptation and Label Unification With Partial Datasets

STEM: An Approach to Multi-Source Domain Adaptation With Guarantees

T-SVDNet: Exploring High-Order Prototypical Correlations for Multi-Source Domain Adaptation

Multi-Source Domain Adaptation for Object Detection

Information-Theoretic Regularization for Multi-Source Domain Adaptation

Partial Feature Selection and Alignment for Multi-Source Domain Adaptation

Wasserstein Barycenter for Multi-Source Domain Adaptation

Unsupervised Multi-source Domain Adaptation Without Access to Source Data

Dynamic Transfer for Multi-Source Domain Adaptation

Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation

MOST: Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

Your Classifier can Secretly Suffice Multi-Source Domain Adaptation

Multi-Source Open-Set Deep Adversarial Domain Adaptation

Online Meta-Learning for Multi-Source and Semi-Supervised Domain Adaptation

Multi-Source Open-Set Deep Adversarial Domain Adaptation

Curriculum Manager for Source Selection in Multi-Source Domain Adaptation

Domain Aggregation Networks for Multi-Source Domain Adaptation

[ECCV2020]

Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation

Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits

Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis

Multi-source Domain Adaptation for Visual Sentiment Classification

Multi-source Distilling Domain Adaptation

Multi-source Domain Adaptation for Semantic Segmentation

Moment Matching for Multi-Source Domain Adaptation

Multi-Domain Adversarial Learning

Algorithms and Theory for Multiple-Source Adaptation

Adversarial Multiple Source Domain Adaptation

Boosting Domain Adaptation by Discovering Latent Domains

Deep Cocktail Network: Multi-source Unsupervised Domain Adaptation with Category Shift

Graphical Modeling for Multi-Source Domain Adaptation

Unsupervised sentiment analysis by transferring multi-source knowledge

A survey of multi-source domain adaptation

Mutual learning network for multi-source domain adaptation

Domain Adaptive Ensemble Learning

Multi-Source Domain Adaptation and Semi-Supervised Domain Adaptation with Focus on Visual Domain Adaptation Challenge 2019

CoNMix for Source-free Single and Multi-target Domain Adaptation

Curriculum Graph Co-Teaching for Multi-Target Domain Adaptation

Multi-Target Domain Adaptation with Collaborative Consistency Learning

Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach

Lifelong Domain Adaptation via Consolidated Internal Distribution

Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning

ConDA: Continual Unsupervised Domain Adaptation

Gradient Regularized Contrastive Learning for Continual Domain Adaptation

Gradual Domain Adaptation without Indexed Intermediate Domains

Learning to Adapt to Evolving Domains

Class-Incremental Domain Adaptation

Incremental Adversarial Domain Adaptation for Continually Changing Environments

Continuous Manifold based Adaptation for Evolving Visual Domains

Adversarial Domain Adaptation for Stance Detection

Ensemble Adversarial Training: Attacks and Defenses

Distant domain transfer learning

Domain Adaptive Classification on Heterogeneous Information Networks

Heterogeneous Domain Adaptation via Soft Transfer Network

Compound Domain Adaptation in an Open World

Domain Agnostic Learning with Disentangled Representations

Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks

Federated Adversarial Domain Adaptation

Continuously Indexed Domain Adaptation

Domain Adaptation with Adversarial Training on Penultimate Activations

Source-free Domain Adaptive Human Pose Estimation

RAIN: RegulArization on Input and Network for Black-Box Domain Adaptation

CoNMix for Source-free Single and Multi-target Domain Adaptation

Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition

Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation

Balancing Discriminability and Transferability for Source-Free Domain Adaptation

Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation

Confident Anchor-Induced Multi-Source Free Domain Adaptation

Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data

Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation

Unsupervised Domain Adaptation of Black-Box Source Models

Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation

Generalized Source-free Domain Adaptation

Adaptive Adversarial Network for Source-free Domain Adaptation

Visualizing Adapted Knowledge in Domain Transfer

Unsupervised Multi-source Domain Adaptation Without Access to Source Data

Source-Free Domain Adaptation for Semantic Segmentation

Domain Impression: A Source Data Free Domain Adaptation Method

Model Adaptation: Unsupervised Domain Adaptation Without Source Data

Universal Source-Free Domain Adaptation

Towards Inheritable Models for Open-Set Domain Adaptation

Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation

Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer

Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer

Local Context-Aware Active Domain Adaptation

Reducing Annotation Effort by Identifying and Labeling Contextually Diverse Classes for Semantic Segmentation Under Domain Shift

Towards Fewer Annotations: Active Learning via Region Impurity and Prediction Uncertainty for Domain Adaptive Semantic Segmentation

Active Learning for Domain Adaptation: An Energy-based Approach

Multi-Anchor Active Domain Adaptation for Semantic Segmentation

Active Domain Adaptation via Clustering Uncertainty-Weighted Embeddings

Active Universal Domain Adaptation

S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation

Transferable Query Selection for Active Domain Adaptation

Generalized Domain Adaptation

Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation

The Balancing Principle for Parameter Choice in Distance-Regularized Domain Adaptation

Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation

Adapting to Distribution Shift by Visual Domain Prompt Generation

Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization

A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation

Improving Single Domain-Generalized Object Detection: A Focus on Diversification and Alignment

Generalization by Adaptation: Diffusion-Based Domain Extension for Domain-Generalized Semantic Segmentation

Topology-aware Robust Optimization for Out-of-Distribution Generalization

A Re-Parameterized Vision Transformer (ReVT) for Domain-Generalized Semantic Segmentation

Weight Averaging Improves Knowledge Distillation under Domain Shift

Adaptive Texture Filtering for Single-Domain Generalized Segmentation

PromptStyler: Prompt-driven Style Generation for Source-free Domain Generalization

Sparse Mixture-of-Experts are Domain Generalizable Learners

Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts

Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation

Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification

Domain Generalization via Inference-time Label-Preserving Target Projections

Domain Generalization via Entropy Regularization

Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization

Learning to Learn with Variational Information Bottleneck for Domain Generalization

Self-Challenging Improves Cross-Domain Generalization

Learning from Extrinsic and Intrinsic Supervisions for Domain Generalization

Learning to Balance Specificity and Invariance for In and Out of Domain Generalization

Learning to Generate Novel Domains for Domain Generalization

Learning to Optimize Domain Specific Normalization for Domain Generalization

Towards Recognizing Unseen Categories in Unseen Domains

Efficient Domain Generalization via Common-Specific Low-Rank Decomposition

Learning to Learn Single Domain Generalization

Generalized Convolutional Forest Networks for Domain Generalization and Visual Recognition

Cross-Domain Few-Shot Classification via Learned Feature-Wise Transformation

Domain Generalization Using a Mixture of Multiple Latent Domains

Deep Domain-Adversarial Image Generation for Domain Generalisation

Domain Generalization via Model-Agnostic Learning of Semantic Features

Episodic Training for Domain Generalization [Pytorch]]( )

Feature-Critic Networks for Heterogeneous Domain Generalization

Domain Generalization by Solving Jigsaw Puzzles

MetaReg: Towards Domain Generalization using Meta-Regularization

Deep Domain Generalization via Conditional Invariant Adversarial Networks

Domain Generalization with Adversarial Feature Learning

Domain Generalization for Regression

Correlation-aware Adversarial Domain Adaptation and Generalization

Adversarial Pyramid Network for Video Domain Generalization

Towards Shape Biased Unsupervised Representation Learning for Domain Generalization

A Generalization Error Bound for Multi-class Domain Generalization

Adversarial Invariant Feature Learning with Accuracy Constraint for Domain Generalization

Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models

DeceptionNet: Network-Driven Domain Randomization

Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization Without Accessing Target Domain Data

Transfer Metric Learning: Algorithms, Applications and Outlooks

Attention Bridging Network for Knowledge Transfer

Few-Shot Image Recognition with Knowledge Transfer

Learning Across Tasks and Domains

UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation

Domain Agnostic Learning with Disentangled Representations

Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization

When Semi-Supervised Learning Meets Transfer Learning: Training Strategies, Models and Datasets

Unsupervised Domain Adaptation of Object Detectors: A Survey

Improving Object Detection via Local-Global Contrastive Learning

Supervision Interpolation via LossMix: Generalizing Mixup for Object Detection and Beyond

Instance Relation Graph Guided Source-Free Domain Adaptive Object Detection

Towards Online Domain Adaptive Object Detection [[

Mixture of Teacher Experts for Source-Free Domain Adaptive Object Detection

Towards Robust Adaptive Object Detection under Noisy Annotations

H FA R-CNN: Holistic and Hierarchical Feature Alignment for Cross-Domain Weakly Supervised Object Detection

Cross-Domain Adaptive Teacher for Object Detection

Task-specific Inconsistency Alignment for Domain Adaptive Object Detection

SIGMA: Semantic-complete Graph Matching for Domain Adaptive Object Detection

Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation

Target-Relevant Knowledge Preservation for Multi-Source Domain Adaptive Object Detection

Cross Domain Object Detection by Target-Perceived Dual Branch Distillation

Decoupled Adaptation for Cross-Domain Object Detection

SCAN: Cross Domain Object Detection with Semantic Conditioned Adaptation

SSAL: Synergizing between Self-Training and Adversarial Learning for Domain Adaptive Object Detection

Multi-Source Domain Adaptation for Object Detection

Knowledge Mining and Transferring for Domain Adaptive Object Detection

Dual Bipartite Graph Learning: A General Approach for Domain Adaptive Object Detection

Seeking Similarities over Differences: Similarity-based Domain Alignment for Adaptive Object Detection

Informative and Consistent Correspondence Mining for Cross-Domain Weakly Supervised Object Detection

MeGA-CDA: Memory Guided Attention for Category-Aware Unsupervised Domain Adaptive Object Detection

SRDAN: Scale-aware and Range-aware Domain Adaptation Network for Cross-dataset 3D Object Detection

I3Net: Implicit Instance-Invariant Network for Adapting One-Stage Object Detectors

RPN Prototype Alignment for Domain Adaptive Object Detector

ST3D: Self-training for Unsupervised Domain Adaptation on 3D ObjectDetection

Domain-Specific Suppression for Adaptive Object Detection

Unbiased Mean Teacher for Cross-Domain Object Detection

YOLO in the Dark - Domain Adaptation Method for Merging Multiple Models

Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection

One-Shot Unsupervised Cross-Domain Detection

Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector

Adapting Object Detectors with Conditional Domain Normalization

Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions

Domain Adaptive Object Detection via Asymmetric Tri-way Faster-RCNN

Cross-domain Object Detection through Coarse-to-Fine Feature Adaptation

Harmonizing Transferability and Discriminability for Adapting Object Detectors

Exploring Categorical Regularization for Domain Adaptive Object Detection

Cross-domain Detection via Graph-induced Prototype Alignment

Multi-spectral Salient Object Detection by Adversarial Domain Adaptation

Deep Domain Adaptive Object Detection: a Survey

Progressive Domain Adaptation for Object Detection

Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night

Self-Training and Adversarial Background Regularization for Unsupervised Domain Adaptive One-Stage Object Detection

A Robust Learning Approach to Domain Adaptive Object Detection

Multi-adversarial Faster-RCNN for Unrestricted Object Detection

Few-Shot Adaptive Faster R-CNN

Exploring Object Relation in Mean Teacher for Cross-Domain Detection

Adapting Object Detectors via Selective Cross-Domain Alignment

Automatic adaptation of object detectors to new domains using self-training

Towards Universal Object Detection by Domain Attention

Strong-Weak Distribution Alignment for Adaptive Object Detection

Diversify and Match: A Domain Adaptive Representation Learning Paradigm for Object Detection

Cross-Domain Weakly-Supervised Object Detection Through Progressive Domain Adaptation

Domain Adaptive Faster R-CNN for Object Detection in the Wild

Cross-domain object detection using unsupervised image translation

Pixel and feature level based domain adaptation for object detection in autonomous driving

See Eye to Eye: A Lidar-Agnostic 3D Detection Framework for Unsupervised Multi-Target Domain Adaptation

Unsupervised Domain Adaptive Object Detection using Forward-Backward Cyclic Adaptation

Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions

Unsupervised Domain Adaptation for Object Detection via Cross-Domain Semi-Supervised Learning

Curriculum Self-Paced Learning for Cross-Domain Object Detection

SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses

PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation

Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions

Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation

DecoupleNet: Decoupled Network for Domain Adaptive Semantic Segmentation

HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation

Style-Hallucinated Dual Consistency Learning for Domain Generalized Semantic Segmentation

DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation

Plugging Self-Supervised Monocular Depth into Unsupervised Domain Adaptation for Semantic Segmentation

Shallow Features Guide Unsupervised Domain Adaptation for Semantic Segmentation at Class Boundaries

Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation

Dual Path Learning for Domain Adaptation of Semantic Segmentation

Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation

Multi-Anchor Active Domain Adaptation for Semantic Segmentation

LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation

Self-Mutating Network for Domain Adaptive Segmentation in Aerial Images

Geometric Unsupervised Domain Adaptation for Semantic Segmentation

Multi-Target Adversarial Frameworks for Domain Adaptation in Semantic Segmentation

BAPA-Net: Boundary Adaptation and Prototype Alignment for Cross-Domain Semantic Segmentation

BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation

Uncertainty-Aware Pseudo Label Refinery for Domain Adaptive Semantic Segmentation

Domain Adaptive Semantic Segmentation With Self-Supervised Depth Estimation

Generalize Then Adapt: Source-Free Domain Adaptive Semantic Segmentation

DARCNN: Domain Adaptive Region-Based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images

DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation

Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation

Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds

Cluster, Split, Fuse, and Update: Meta-Learning for Open Compound Domain Adaptive Semantic Segmentation

PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training

Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation

Cross-View Regularization for Domain Adaptive Panoptic Segmentation

Semi-supervised Domain Adaptation based on Dual-level Domain Mixing for Semantic Segmentation

MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation

Coarse-to-Fine Domain Adaptive Semantic Segmentation with Photometric Alignment and Category-Center Regularization

Multi-Source Domain Adaptation with Collaborative Learning for Semantic Segmentation

Source-Free Domain Adaptation for Semantic Segmentation

Instance Adaptive Self-Training for Unsupervised Domain Adaptation

Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning

Pixel-Level Cycle Association: A New Perspective for Domain Adaptive Semantic Segmentation

Adversarial Style Mining for One-Shot Unsupervised Domain Adaptation

Semantically Adaptive Image-to-image Translation for Domain Adaptation of Semantic Segmentation

Contextual-Relation Consistent Domain Adaptation for Semantic Segmentation

Learning from Scale-Invariant Examples for Domain Adaptation in Semantic Segmentation

Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation

Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search

Domain Adaptive Semantic Segmentation Using Weak Labels

Content-Consistent Matching for Domain Adaptive Semantic Segmentation

Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer

Phase Consistent Ecological Domain Adaptation

FDA: Fourier Domain Adaptation for Semantic Segmentation

Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting

Unsupervised Intra-domain Adaptation for Semantic Segmentation through Self-Supervision

Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

Learning Texture Invariant Representation for Domain Adaptation of Semantic Segmentation

xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation

Unsupervised Scene Adaptation with Memory Regularization in vivo

Joint Adversarial Learning for Domain Adaptation in Semantic Segmentation

An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation

Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation

MLSL: Multi-Level Self-Supervised Learning for Domain Adaptation with Spatially Independent and Semantically Consistent Labeling

Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation

Guided Curriculum Model Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation

Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach

SSF-DAN: Separated Semantic Feature Based Domain Adaptation Network for Semantic Segmentation

Significance-aware Information Bottleneck for Domain Adaptive Semantic Segmentation

Domain Adaptation for Semantic Segmentation with Maximum Squares Loss

Self-Ensembling with GAN-based Data Augmentation for Domain Adaptation in Semantic Segmentation

DADA: Depth-aware Domain Adaptation in Semantic Segmentation

Domain Adaptation for Structured Output via Discriminative Patch Representations

Not All Areas Are Equal: Transfer Learning for Semantic Segmentation via Hierarchical Region Selection

CrDoCo: Pixel-level Domain Transfer with Cross-Domain Consistency

Bidirectional Learning for Domain Adaptation of Semantic Segmentation

Learning Semantic Segmentation from Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach

All about Structure: Adapting Structural Information across Domains for Boosting Semantic Segmentation

DLOW: Domain Flow for Adaptation and Generalization

Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation

ADVENT: Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

SPIGAN: Privileged Adversarial Learning from Simulation

Penalizing Top Performers: Conservative Loss for Semantic Segmentation Adaptation

Domain transfer through deep activation matching

Unsupervised Domain Adaptation for Semantic Segmentation via Class-Balanced Self-Training

DCAN: Dual channel-wise alignment networks for unsupervised scene adaptation

Fully convolutional adaptation networks for semantic segmentation

Learning to Adapt Structured Output Space for Semantic Segmentation

Conditional Generative Adversarial Network for Structured Domain Adaptation

Learning From Synthetic Data: Addressing Domain Shift for Semantic Segmentation

Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes

No more discrimination: Cross city adaptation of road scene segmenters

SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation

Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation

Rectifying Pseudo Label Learning via Uncertainty Estimation for Domain Adaptive Semantic Segmentation

Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet

Affinity Space Adaptation for Semantic Segmentation Across Domains

Semantic-aware short path adversarial training for cross-domain semantic segmentation

Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes

Class-Conditional Domain Adaptation on Semantic Segmentation

Adversarial Learning and Self-Teaching Techniques for Domain Adaptation in Semantic Segmentation

FCNs in the Wild: Pixel-level Adversarial and Constraint-based Adaptation

BoMuDA: Boundless Multi-Source Domain Adaptive Segmentation in Unconstrained Environments

SAfE: Self-Attention Based Unsupervised Road Safety Classification in Hazardous Environments

Semantics-aware Multi-modal Domain Translation:From LiDAR Point Clouds to Panoramic Color Images

Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification

Group-aware Label Transfer for Domain Adaptive Person Re-identification

Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification

Joint Visual and Temporal Consistency for Unsupervised Domain Adaptive Person Re-Identification

Joint Disentangling and Adaptation for Cross-Domain Person Re-Identification

Multiple Expert Brainstorming for Domain Adaptive Person Re-identification

Deep Credible Metric Learning for Unsupervised Domain Adaptation Person Re-identification

Unsupervised Domain Adaptation with Noise Resistible Mutual-Training for Person Re-identification

Generalizing Person Re-Identification by Camera-Aware Invariance Learning and Cross-Domain Mixup

AD-Cluster: Augmented Discriminative Clustering for Domain Adaptive Person Re-identification

Smoothing Adversarial Domain Attack and P-Memory Reconsolidation for Cross-Domain Person Re-Identification

Cross-Modal Cross-Domain Moment Alignment Network for Person Search

Online Joint Multi-Metric Adaptation From Frequent Sharing-Subset Mining for Person Re-Identification

Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification

Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification

A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification

Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification

Domain Adaptation through Synthesis for Unsupervised Person Re-identification

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification

Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning

Structured Domain Adaptation for Unsupervised Person Re-identification

Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification

Camera Adversarial Transfer for Unsupervised Person Re-Identification

EANet: Enhancing Alignment for Cross-Domain Person Re-identification

One Shot Domain Adaptation for Person Re-Identification

Similarity-preserving Image-image Domain Adaptation for Person Re-identification

DIRL: Domain-Invariant Reperesentation Learning Approach for Sim-to-Real Transfer

Overcoming Label Noise for Source-free Unsupervised Video Domain Adaptation [[ICVGIP'22]] ( ) [Pytorch]]( ) [[Project]] ( ) [[Extended Version]] ( )

Source-free Video Domain Adaptation by Learning Temporal Consistency for Action Recognition

Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing

Learning Cross-Modal Contrastive Features for Video Domain Adaptation

Partial Video Domain Adaptation With Partial Adversarial Temporal Attentive Network

Domain Adaptive Video Segmentation via Temporal Consistency Regularization

Shuffle and Attend: Video Domain Adaptation

Transferring Cross-Domain Knowledge for Video Sign Language Recognition

Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation

Transferring Cross-domain Knowledge for Video Sign Language Recognition

Multi-Modal Domain Adaptation for Fine-Grained Action Recognition

Adversarial Cross-Domain Action Recognition with Co-Attention

Generative Adversarial Networks for Video-to-Video Domain Adaptation

Temporal Attentive Alignment for Large-Scale Video Domain Adaptation

Temporal Attentive Alignment for Video Domain Adaptation

Video Unsupervised Domain Adaptation with Deep Learning: A Comprehensive Survey

Unsupervised Video Domain Adaptation: A Disentanglement Perspective

Image to Video Domain Adaptation Using Web Supervision

PopGenAdapt: Semi-Supervised Domain Adaptation for Genotype-to-Phenotype Prediction in Underrepresented Populations

Cross-stained Segmentation from Renal Biopsy Images Using Multi-level Adversarial Learning

What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation

Semantic-Transferable Weakly-Supervised Endoscopic Lesions Segmentation

Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet

On-the-Fly Test-time Adaptation for Medical Image Segmentation

Target and task specific source-free domain adaptive image segmentation

Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation

Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

Unsupervised domain adaptation for medical imaging segmentation with self-ensembling

Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation

Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer

SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation

Sparse-to-Dense Feature Matching: Intra and Inter Domain Cross-Modal Learning in Domain Adaptation for 3D Semantic Segmentation

Unsupervised Domain Adaptive 3D Detection With Multi-Level Consistency

Domain-Adaptive Single-View 3D Reconstruction

MS3D++: Ensemble of Experts for Multi-Source Unsupervised Domain Adaptation in 3D Object Detection

Progressive Adversarial Networks for Fine-Grained Domain Adaptation

SALUDA: Surface-based Automotive Lidar Unsupervised Domain Adaptation

GIPSO: Geometrically Informed Propagation for Online Adaptation in 3D LiDAR Segmentation

CoSMix: Compositional Semantic Mix for Domain Adaptation in 3D LiDAR Segmentation

ConDA: Unsupervised Domain Adaptation for LiDAR Segmentation via Regularized Domain Concatenation

Open-Set Black-Box Domain Adaptation for Remote Sensing Image Scene Classification

RefRec: Pseudo-labels Refinement via Shape Reconstruction for Unsupervised 3D Domain Adaptation

Unsupervised Domain Adaptation in LiDAR Semantic Segmentation with Self-Supervision and Gated Adapters

RDA: Robust Domain Adaptation via Fourier Adversarial Attacking

Geometry-Aware Self-Training for Unsupervised Domain Adaptation on Object Point Clouds

Tune It the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density

PIT: Position-Invariant Transform for Cross-FoV Domain Adaptation

Self-Supervised Domain Adaptation for Forgery Localization of JPEG Compressed Images

Unsupervised Real-World Super-Resolution: A Domain Adaptation Perspective

Adversarial Robustness for Unsupervised Domain Adaptation

Collaborative Optimization and Aggregation for Decentralized Domain Generalization and Adaptation

Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval

Spatio-temporal Contrastive Domain Adaptation for Action Recognition

Regressive Domain Adaptation for Unsupervised Keypoint Detection

From Synthetic to Real: Unsupervised Domain Adaptation for Animal Pose Estimation

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

[NeurlPS 2020]

Adapting Neural Architectures Between Domains

Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition

A Broader Study of Cross-Domain Few-Shot Learning

Label-Noise Robust Domain Adaptation

Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model

Domain Adaptation for Semantic Parsing

Bridging Cross-Tasks Gap for Cognitive Assessment via Fine-Grained Domain Adaptation

Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation

Weakly-Supervised Domain Adaptation via GAN and Mesh Model for Estimating 3D Hand Poses Interacting Objects

One-Shot Domain Adaptation for Face Generation

Learning Meta Face Recognition in Unseen Domains

Cross-Domain Document Object Detection: Benchmark Suite and Method

StereoGAN: Bridging Synthetic-to-Real Domain Gap by Joint Optimization of Domain Translation and Stereo Matching

Domain Adaptation for Image Dehazing

Probability Weighted Compact Feature for Domain Adaptive Retrieval

Disparity-Aware Domain Adaptation in Stereo Image Restoration

Multi-Path Learning for Object Pose Estimation Across Domains

Unsupervised Domain Adaptation for 3D Human Pose Estimation

PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation

Deep Head Pose Estimation Using Synthetic Images and Partial Adversarial Domain Adaption for Continuous Label Spaces

Cross-Domain Adaptation for Animal Pose Estimation

GA-DAN: Geometry-Aware Domain Adaptation Network for Scene Text Detection and Recognition

Accelerating Deep Unsupervised Domain Adaptation with Transfer Channel Pruning

Adversarial Adaptation of Scene Graph Models for Understanding Civic Issues

Cross-Dataset Adaptation for Visual Question Answering

Cross-domain fault diagnosis through optimal transport for a CSTR process

DASGIL: Domain Adaptation for Semantic and Geometric-Aware Image-Based Localization

An Unsupervised Domain Adaptation Scheme for Single-Stage Artwork Recognition in Cultural Sites

Multi-source transfer learning of time series in cyclical manufacturing

Domain adaptation for regression under Beer-Lambert's law

Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation

DANE: Domain Adaptive Network Embedding

Active Adversarial Domain Adaptation

Kurcuma: a kitchen utensil recognition collection for unsupervised domain adaptation

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark

LLVIP: A Visible-infrared Paired Dataset for Low-light Vision

Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation

Benchmarking Neural Network Robustness to Common Corruptions and Perturbations (ImageNet-C)

A Primer on Domain Adaptation