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 26012650 of 6439 papers

TitleStatusHype
Few-shot Unsupervised Domain Adaptation with Image-to-class Sparse Similarity Encoding0
Attentional Road Safety Networks0
Filter-based Discriminative Autoencoders for Children Speech Recognition0
Filtered Manifold Alignment0
GoodSAM: Bridging Domain and Capacity Gaps via Segment Anything Model for Distortion-aware Panoramic Semantic Segmentation0
Financial Aspect-Based Sentiment Analysis using Deep Representations0
Finding Answers from the Word of God: Domain Adaptation for Neural Networks in Biblical Question Answering0
Findings of the 2014 Workshop on Statistical Machine Translation0
Findings of the LoResMT 2020 Shared Task on Zero-Shot for Low-Resource languages0
Findings of the Second Workshop on Neural Machine Translation and Generation0
GPLAC: Generalizing Vision-Based Robotic Skills using Weakly Labeled Images0
Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translation0
Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translation0
Exploiting weakly-labeled Web images to improve object classification: a domain adaptation approach0
Coping with low data availability for social media crisis message categorisation0
Fine-grained Interpretation and Causation Analysis in Deep NLP Models0
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation0
Fine-grained Recognition in the Wild: A Multi-Task Domain Adaptation Approach0
Exploiting Semantics in Adversarial Training for Image-Level Domain Adaptation0
Fine-grained Unsupervised Domain Adaptation for Gait Recognition0
ATPL: Mutually enhanced adversarial training and pseudo labeling for unsupervised domain adaptation0
Finetuning Foundation Models for Joint Analysis Optimization0
Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection0
Fine-tuning Large Language Models for Domain-specific Machine Translation0
Adapting Models to Signal Degradation using Distillation0
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER0
Exploiting Neural Query Translation into Cross Lingual Information Retrieval0
A Unified Framework for Heterogeneous Semi-supervised Learning0
Exploiting Negative Learning for Implicit Pseudo Label Rectification in Source-Free Domain Adaptive Semantic Segmentation0
FJWU Participation for the WMT21 Biomedical Translation Task0
Exploiting Local Feature Patterns for Unsupervised Domain Adaptation0
Implicit Steganography Beyond the Constraints of Modality0
Flexible deep transfer learning by separate feature embeddings and manifold alignment0
Flexible Domain Adaptation for Automated Essay Scoring Using Correlated Linear Regression0
Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages0
FLORS: Fast and Simple Domain Adaptation for Part-of-Speech Tagging0
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models0
Flow Graph Corpus from Recipe Texts0
Exploiting Language Relatedness in Machine Translation Through Domain Adaptation Techniques0
A Theory of Output-Side Unsupervised Domain Adaptation0
Fluid Annotation: A Granularity-aware Annotation Tool for Chinese Word Fluidity0
Cross-Domain Few-Shot Classification via Inter-Source Stylization0
Collaborative Multi-source Domain Adaptation Through Optimal Transport0
Focused training sets to reduce noise in NER feature models0
A Comprehensive Survey on Source-free Domain Adaptation0
Focus on Semantic Consistency for Cross-domain Crowd Understanding0
Focus on Your Target: A Dual Teacher-Student Framework for Domain-adaptive Semantic Segmentation0
FODA-PG for Enhanced Medical Imaging Narrative Generation: Adaptive Differentiation of Normal and Abnormal Attributes0
Exploiting Inter-Sample Affinity for Knowability-Aware Universal Domain Adaptation0
Exploiting Inter-pixel Correlations in Unsupervised Domain Adaptation for Semantic Segmentation0
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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