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
Effective Use of Target-side Context for Neural Machine Translation0
Effect of Kinematics and Fluency in Adversarial Synthetic Data Generation for ASL Recognition with RF Sensors0
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift0
Efficient Annotation and Learning for 3D Hand Pose Estimation: A Survey0
Efficient Black-Box Speaker Verification Model Adaptation with Reprogramming and Backend Learning0
Efficient Convolutional Neural Networks for Depth-Based Multi-Person Pose Estimation0
Efficient Data Selection for Domain Adaptation of ASR Using Pseudo-Labels and Multi-Stage Filtering0
Efficient Deep Neural Networks0
Efficient Discrepancy Testing for Learning with Distribution Shift0
Efficient Domain Adaptation for Endoscopic Visual Odometry0
Efficient Domain Adaptation for Speech Foundation Models0
Efficient Domain Adaptation of Language Models via Adaptive Tokenization0
Prompt-tuning in ASR systems for efficient domain-adaptation0
Efficient Domain Adaptation of Multimodal Embeddings using Constrastive Learning0
Efficient Domain Adaptation of Sentence Embeddings Using Adapters0
Efficient Extraction of Pseudo-Parallel Sentences from Raw Monolingual Data Using Word Embeddings0
Efficient Fine-Tuning with Domain Adaptation for Privacy-Preserving Vision Transformer0
Efficient Hierarchical Domain Adaptation for Pretrained Language Models0
Efficient Machine Translation Domain Adaptation0
Efficient Model Adaptation for Continual Learning at the Edge0
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement0
Efficient Supervision for Robot Learning via Imitation, Simulation, and Adaptation0
Efficient Unsupervised Domain Adaptation Regression for Spatial-Temporal Air Quality Sensor Fusion0
Efficient Utilization of Large Pre-Trained Models for Low Resource ASR0
Effort of Genre Variation and Prediction of System Performance0
EF-Train: Enable Efficient On-device CNN Training on FPGA Through Data Reshaping for Online Adaptation or Personalization0
EGFormer: Towards Efficient and Generalizable Multimodal Semantic Segmentation0
ET-GAN: Cross-Language Emotion Transfer Based on Cycle-Consistent Generative Adversarial Networks0
Elastic Information Bottleneck0
ELF-UA: Efficient Label-Free User Adaptation in Gaze Estimation0
ElimPCL: Eliminating Noise Accumulation with Progressive Curriculum Labeling for Source-Free Domain Adaptation0
ELSA: Efficient Label Shift Adaptation through the Lens of Semiparametric Models0
Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction0
Embedding Space Correlation as a Measure of Domain Similarity0
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation0
Emergence of Implicit World Models from Mortal Agents0
Emotional Semantics-Preserved and Feature-Aligned CycleGAN for Visual Emotion Adaptation0
Emotion-guided Cross-domain Fake News Detection using Adversarial Domain Adaptation0
Emotion Recognition from Multiple Modalities: Fundamentals and Methodologies0
EMPL: A novel Efficient Meta Prompt Learning Framework for Few-shot Unsupervised Domain Adaptation0
Employing Word Representations and Regularization for Domain Adaptation of Relation Extraction0
EMTL: A Generative Domain Adaptation Approach0
Enabling Heterogeneous Domain Adaptation in Multi-inhabitants Smart Home Activity Learning0
Encoder Adaptation of Dense Passage Retrieval for Open-Domain Question Answering0
Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation0
EndoUDA: A modality independent segmentation approach for endoscopy imaging0
End-to-End Lip Reading in Romanian with Cross-Lingual Domain Adaptation and Lateral Inhibition0
End-to-End Neural Speaker Diarization with Permutation-Free Objectives0
End-to-End QA on COVID-19: Domain Adaptation with Synthetic Training0
End-to-End Race Driving with Deep Reinforcement Learning0
Show:102550
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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