SOTAVerified

Domain Adaptation

Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Further readings:

( Image credit: Unsupervised Image-to-Image Translation Networks )

Papers

Showing 56015650 of 6439 papers

TitleStatusHype
Task Driven Generative Modeling for Unsupervised Domain Adaptation: Application to X-ray Image Segmentation0
Cross-Dataset Adaptation for Visual Question Answering0
Findings of the Second Workshop on Neural Machine Translation and Generation0
#SarcasmDetection is soooo general! Towards a Domain-Independent Approach for Detecting Sarcasm0
Embedding Transfer for Low-Resource Medical Named Entity Recognition: A Case Study on Patient MobilityCode0
A Comparative Study on Unsupervised Domain Adaptation Approaches for Coffee Crop Mapping0
Factorized Adversarial Networks for Unsupervised Domain Adaptation0
Adversarial Domain Adaptation for Classification of Prostate Histopathology Whole-Slide Images0
Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-ray Segmentation0
Coupled End-to-End Transfer Learning With Generalized Fisher Information0
Real-Time Monocular Depth Estimation Using Synthetic Data With Domain Adaptation via Image Style TransferCode1
Temporal Hallucinating for Action Recognition With Few Still Images0
Re-Weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation0
Collaborative and Adversarial Network for Unsupervised Domain AdaptationCode0
Conditional Generative Adversarial Network for Structured Domain Adaptation0
Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation0
Deep Face Detector Adaptation Without Negative Transfer or Catastrophic Forgetting0
Duplex Generative Adversarial Network for Unsupervised Domain Adaptation0
Solving Feature Sparseness in Text Classification using Core-Periphery Decomposition0
YNU-HPCC at SemEval-2018 Task 1: BiLSTM with Attention based Sentiment Analysis for Affect in Tweets0
Learning Hidden Unit Contribution for Adapting Neural Machine Translation Models0
Improve Neural Entity Recognition via Multi-Task Data Selection and Constrained Decoding0
Bag of Experts Architectures for Model Reuse in Conversational Language Understanding0
Pivot Based Language Modeling for Improved Neural Domain Adaptation0
Domain Adaptation for MRI Organ Segmentation using Reverse Classification AccuracyCode0
A Survey of Domain Adaptation for Neural Machine Translation0
One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networksCode0
Learning Factorized Representations for Open-set Domain Adaptation0
Robust Place Categorization with Deep Domain GeneralizationCode0
AdapterNet - learning input transformation for domain adaptation0
K-Beam Minimax: Efficient Optimization for Deep Adversarial LearningCode0
Unsupervised Domain Adaptation using Regularized Hyper-graph Matching0
DiDA: Disentangled Synthesis for Domain Adaptation0
Learning Sampling Policies for Domain Adaptation0
An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identification0
What's in a Domain? Learning Domain-Robust Text Representations using Adversarial TrainingCode0
Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated ExamplesCode0
Fast Retinomorphic Event Stream for Video Recognition and Reinforcement Learning0
Visual Representations for Semantic Target Driven NavigationCode0
A La Carte Embedding: Cheap but Effective Induction of Semantic Feature VectorsCode0
Domain Adaptation with Adversarial Training and Graph EmbeddingsCode0
BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask LearningCode1
Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks0
Semi-Supervised Domain Adaptation with Representation Learning for Semantic Segmentation across Time0
Unpaired Multi-Domain Image Generation via Regularized Conditional GANsCode0
Transferring GANs: generating images from limited dataCode0
Boosting Domain Adaptation by Discovering Latent DomainsCode0
Multi-label Learning Based Deep Transfer Neural Network for Facial Attribute Classification0
Multilingual Parallel Corpus for Global Communication Plan0
Experiments with Convolutional Neural Networks for Multi-Label Authorship AttributionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FFTATAverage Accuracy96Unverified
2PMTransAverage Accuracy95.3Unverified
3CMKDAverage Accuracy94.4Unverified
4SSRT-B (ours)Average Accuracy93.5Unverified
5CDTransAverage Accuracy92.6Unverified
6CoViAverage Accuracy91.8Unverified
7GSDEAverage Accuracy91.7Unverified
8FixBiAverage Accuracy91.4Unverified
9Contrastive Adaptation NetworkAverage Accuracy90.6Unverified
10BIWAAAverage Accuracy90.5Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU78.1Unverified
2ILM-ASSLmIoU76.6Unverified
3DCFmIoU69.3Unverified
4HRDA+PiPamIoU68.2Unverified
5MICmIoU67.3Unverified
6FREDOM - TransformermIoU67Unverified
7HRDAmIoU65.8Unverified
8SePiComIoU64.3Unverified
9MIC + Guidance TrainingmIoU63.8Unverified
10DAFormer + ProCSTmIoU61.6Unverified
#ModelMetricClaimedVerifiedStatus
1HALOmIoU77.8Unverified
2DCFmIoU77.7Unverified
3ILM-ASSLmIoU76.1Unverified
4MICmIoU75.9Unverified
5HRDA+PiPamIoU75.6Unverified
6HRDAmIoU73.8Unverified
7FREDOM - TransformermIoU73.6Unverified
8HALOmIoU73.3Unverified
9SePiComIoU70.3Unverified
10DAFormer + ProCSTmIoU69.4Unverified
#ModelMetricClaimedVerifiedStatus
1SWGAccuracy92.3Unverified
2RCLAccuracy90Unverified
3PGA (ViT-L/14)Accuracy89.4Unverified
4PMTransAccuracy89Unverified
5CMKDAccuracy89Unverified
6MICAccuracy86.2Unverified
7PGA (ViT-B/16)Accuracy85.1Unverified
8ELSAccuracy84.6Unverified
9SDAT (ViT-B/16)Accuracy84.3Unverified
10CDTrans (DeiT-B)Accuracy80.5Unverified
#ModelMetricClaimedVerifiedStatus
1FFTATAccuracy93.8Unverified
2RCLAccuracy93.2Unverified
3MICAccuracy92.8Unverified
4SWGAccuracy92.7Unverified
5CMKDAccuracy91.8Unverified
6DePTAccuracy90.7Unverified
7SDAT(ViT)Accuracy89.8Unverified
8SFDA2++Accuracy89.6Unverified
9PMtransAccuracy88.8Unverified
10CoViAccuracy88.5Unverified
#ModelMetricClaimedVerifiedStatus
1CMKDAccuracy94.3Unverified
2MCC+NWDAccuracy90.7Unverified
3GLOT-DRAccuracy90.4Unverified
4SPLAccuracy90.3Unverified
5DFA-SAFNAccuracy90.2Unverified
6DADAAccuracy89.3Unverified
7DFA-ENTAccuracy89.1Unverified
8MEDMAccuracy88.9Unverified
9DDAAccuracy88.9Unverified
10IAFN+ENTAccuracy88.9Unverified
#ModelMetricClaimedVerifiedStatus
1SoRAmIoU78.8Unverified
2ReinmIoU77.6Unverified
3CoDAmIoU72.6Unverified
4Refign (HRDA)mIoU72.1Unverified
5HALOmIoU71.9Unverified
6MICmIoU70.4Unverified
7HRDAmIoU68Unverified
8Refign (DAFormer)mIoU65.5Unverified
9VBLC (DAFormer)mIoU64.2Unverified
10CMFormermIoU60.1Unverified
#ModelMetricClaimedVerifiedStatus
1FACTAccuracy98.8Unverified
2FAMCDAccuracy98.72Unverified
3DFA-MCDAccuracy98.6Unverified
4Mean teacherAccuracy98.26Unverified
5DRANetAccuracy98.2Unverified
6SHOTAccuracy98Unverified
7DFA-ENTAccuracy97.9Unverified
8CyCleGAN (Light-weight Calibrator)Accuracy97.1Unverified