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 49515000 of 6439 papers

TitleStatusHype
Multi-task Domain Adaptation for Sequence Tagging0
Multi-Task Learning for Automotive Foggy Scene Understanding via Domain Adaptation to an Illumination-Invariant Representation0
Multi-Task Supervised Pretraining for Neural Domain Adaptation0
Multivariate Regression on the Grassmannian for Predicting Novel Domains0
Multiview Contrastive Learning for Unsupervised Domain Adaptation in Brain–Computer Interfaces0
Multi-View Domain Generalization for Visual Recognition0
Museum Exhibit Identification Challenge for Domain Adaptation and Beyond0
Museum Exhibit Identification Challenge for the Supervised Domain Adaptation and Beyond0
Mutual Learning for Domain Adaptation: Self-distillation Image Dehazing Network with Sample-cycle0
Mutual Learning Network for Multi-Source Domain Adaptation0
Mutual Regression Distance0
MVP: Meta Visual Prompt Tuning for Few-Shot Remote Sensing Image Scene Classification0
Mx2M: Masked Cross-Modality Modeling in Domain Adaptation for 3D Semantic Segmentation0
My Health Sensor, my Classifier: Adapting a Trained Classifier to Unlabeled End-User Data0
NAIST's Machine Translation Systems for IWSLT 2020 Conversational Speech Translation Task0
Named-Entity Tagging and Domain adaptation for Better Customized Translation0
Natural Language Inference with Definition Embedding Considering Context On the Fly0
Naver Labs Europe's Systems for the WMT19 Machine Translation Robustness Task0
Navigation-Based Candidate Expansion and Pretrained Language Models for Citation Recommendation0
NDP: Next Distribution Prediction as a More Broad Target0
Neighbor Class Consistency on Unsupervised Domain Adaptation0
Neocortical plasticity: an unsupervised cake but no free lunch0
NeRF-Gaze: A Head-Eye Redirection Parametric Model for Gaze Estimation0
Nested Named Entity Recognition as Corpus Aware Holistic Structure Parsing0
Nested Named Entity Recognition as Holistic Structure Parsing0
Network Architecture Search for Domain Adaptation0
Filter Distillation for Network Compression0
NETWORK COMPRESSION USING CORRELATION ANALYSIS OF LAYER RESPONSES0
Neural domain alignment for spoken language recognition based on optimal transport0
Neural Lattice Search for Domain Adaptation in Machine Translation0
Neural Machine Translation Models Can Learn to be Few-shot Learners0
Neural Network for Heterogeneous Annotations0
Neural Personalized Response Generation as Domain Adaptation0
Neural Regularized Domain Adaptation for Chinese Word Segmentation0
Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units0
Neural Task Success Classifiers for Robotic Manipulation from Few Real Demonstrations0
Neural vs. Phrase-Based Machine Translation in a Multi-Domain Scenario0
NeuroADDA: Active Discriminative Domain Adaptation in Connectomic0
Neuronal Cell Type Classification using Deep Learning0
Neuron-level Interpretation of Deep NLP Models: A Survey0
Neutral residues: revisiting adapters for model extension0
Newer is not always better: Rethinking transferability metrics, their peculiarities, stability and performance0
New Transfer Learning Techniques for Disparate Label Sets0
N-Gram Nearest Neighbor Machine Translation0
NICT-2 Translation System for WAT2016: Applying Domain Adaptation to Phrase-based Statistical Machine Translation0
NICT Kyoto Submission for the WMT’20 Quality Estimation Task: Intermediate Training for Domain and Task Adaptation0
NICT's participation to WAT 2019: Multilingualism and Multi-step Fine-Tuning for Low Resource NMT0
NICT's Supervised Neural Machine Translation Systems for the WMT19 Translation Robustness Task0
NightCC: Nighttime Color Constancy via Adaptive Channel Masking0
NI-UDA: Graph Adversarial Domain Adaptation from Non-shared-and-Imbalanced Big Data to Small Imbalanced Applications0
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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