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 54515500 of 6439 papers

TitleStatusHype
Progressive Memory Banks for Incremental Domain AdaptationCode0
Transferable Positive/Negative Speech Emotion Recognition via Class-wise Adversarial Domain Adaptation0
Unsupervised Multi-Target Domain Adaptation: An Information Theoretic Approach0
Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering0
Improving Document Binarization via Adversarial Noise-Texture AugmentationCode0
Tackling Sequence to Sequence Mapping Problems with Neural Networks0
Domain Adaptive Segmentation in Volume Electron Microscopy ImagingCode0
Robust Domain Adaptation By Augmented Cyclic Adversarial Learning0
DASED: A Multi-Domain Dataset for Sound Event Detection Domain Adaptation0
Revisiting Distributional Correspondence Indexing: A Python Reimplementation and New ExperimentsCode0
Domain Adaptation for Semantic Segmentation via Class-Balanced Self-TrainingCode0
Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images: An Adversarial Approach0
Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation0
Neural Adaptation Layers for Cross-domain Named Entity RecognitionCode0
Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation0
A Novel Domain Adaptation Framework for Medical Image Segmentation0
Domain Confusion with Self Ensembling for Unsupervised Adaptation0
SPIGAN: Privileged Adversarial Learning from Simulation0
Seeing Beyond Appearance - Mapping Real Images into Geometrical Domains for Unsupervised CAD-based Recognition0
Transferring Physical Motion Between Domains for Neural Inertial Tracking0
Unsupervised Adversarial Visual Level Domain Adaptation for Learning Video Object Detectors from ImagesCode0
Fast Approach to Build an Automatic Sentiment Annotator for Legal Domain using Transfer Learning0
A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation0
LMU Munich's Neural Machine Translation Systems at WMT 20180
Syntax-based Transfer Learning for the Task of Biomedical Relation Extraction0
Exploring Named Entity Recognition As an Auxiliary Task for Slot Filling in Conversational Language Understanding0
Cross-Domain Detection of Abusive Language Online0
Translation of Biomedical Documents with Focus on Spanish-English0
Hunter NMT System for WMT18 Biomedical Translation Task: Transfer Learning in Neural Machine Translation0
An Unsupervised System for Parallel Corpus Filtering0
Detecting Diabetes Risk from Social Media Activity0
Transferring from Formal Newswire Domain with Hypernet for Twitter POS Tagging0
Modeling Temporality of Human Intentions by Domain Adaptation0
Improving the Generalization of Adversarial Training with Domain AdaptationCode0
Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving0
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces0
Real Time Monitoring of Social Media and Digital Press0
Semi-supervised Learning with Multi-Domain Sentiment Word Embeddings0
DOMAIN ADAPTATION VIA DISTRIBUTION AND REPRESENTATION MATCHING: A CASE STUDY ON TRAINING DATA SELECTION VIA REINFORCEMENT LEARNING0
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation LearningCode0
Unsupervised Adversarial Invariance0
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain AdaptationCode0
Domain Adaptation for Robot Predictive Maintenance Systems0
SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point CloudCode0
Deep Domain Adaptation under Deep Label Scarcity0
Understanding Behavior of Clinical Models under Domain Shifts0
Generative Adversarial Network in Medical Imaging: A ReviewCode2
Sensor Transfer: Learning Optimal Sensor Effect Image Augmentation for Sim-to-Real Domain Adaptation0
Style Augmentation: Data Augmentation via Style RandomizationCode0
A Domain Agnostic Normalization Layer for Unsupervised Adversarial Domain Adaptation0
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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
4CMKDAccuracy89Unverified
5PMTransAccuracy89Unverified
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
8DDAAccuracy88.9Unverified
9MEDMAccuracy88.9Unverified
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