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 52015250 of 6439 papers

TitleStatusHype
Domain Adaptation for Syntactic and Semantic Dependency Parsing Using Deep Belief Networks0
Domain Adaptation for Time series Transformers using One-step fine-tuning0
Domain Adaptation for Ultrasound Beamforming0
Domain Adaptation for Unknown Image Distortions in Instance Segmentation0
Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data0
Domain Adaptation for Visual Applications: A Comprehensive Survey0
Domain Adaptation Framework for Turning Movement Count Estimation with Limited Data0
Domain Adaptation from Synthesis to Reality in Single-model Detector for Video Smoke Detection0
Domain Adaptation from User-level Facebook Models to County-level Twitter Predictions0
Domain Adaptation Gaze Estimation by Embedding with Prediction Consistency0
Domain Adaptation in 3D Object Detection with Gradual Batch Alternation Training0
Domain Adaptation in Agricultural Image Analysis: A Comprehensive Review from Shallow Models to Deep Learning0
Domain Adaptation in Dialogue Systems using Transfer and Meta-Learning0
Domain Adaptation in Highly Imbalanced and Overlapping Datasets0
Domain Adaptation in LiDAR Semantic Segmentation by Aligning Class Distributions0
Domain Adaptation in MT Using Titles in Wikipedia as a Parallel Corpus: Resources and Evaluation0
Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identification0
Domain Adaptation in Multi-View Embedding for Cross-Modal Video Retrieval0
Domain Adaptation in Neural Machine Translation using a Qualia-Enriched FrameNet0
Domain adaptation in practice: Lessons from a real-world information extraction pipeline0
Domain Adaptation for Robot Predictive Maintenance Systems0
Domain adaptation in small-scale and heterogeneous biological datasets0
Domain Adaptation: Learning Bounds and Algorithms0
Domain Adaptation Meets Disentangled Representation Learning and Style Transfer0
Domain Adaptation meets Individual Fairness. And they get along0
Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation0
Domain adaptation model for retinopathy detection from cross-domain OCT images0
Domain Adaptation of a Dependency Parser with a Class-Class Selectional Preference Model0
Domain Adaptation on Semantic Segmentation for Aerial Images0
Domain Adaptation of a State of the Art Text-to-SQL Model: Lessons Learned and Challenges Found0
Domain Adaptation of Automated Treatment Planning from Computed Tomography to Magnetic Resonance0
Domain Adaptation of Coreference Resolution for Radiology Reports0
Domain Adaptation of Document-Level NMT in IWSLT190
Domain Adaptation of Foundation LLMs for e-Commerce0
Domain Adaptation of Learned Features for Visual Localization0
Domain Adaptation of Llama3-70B-Instruct through Continual Pre-Training and Model Merging: A Comprehensive Evaluation0
Domain Adaptation of low-resource Target-Domain models using well-trained ASR Conformer Models0
Domain Adaptation of Machine Translation with Crowdworkers0
Domain Adaptation of Majority Votes via Perturbed Variation-based Label Transfer0
Domain Adaptation of Multilingual Semantic Search - Literature Review0
Domain Adaptation of NMT models for English-Hindi Machine Translation Task at AdapMT ICON 20200
Domain Adaptation of NMT models for English-Hindi Machine Translation Task : AdapMT Shared Task ICON 20200
Domain Adaptation of Polarity Lexicon combining Term Frequency and Bootstrapping0
Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding0
Domain Adaptation of Reinforcement Learning Agents based on Network Service Proximity0
Domain-adaptation of spherical embeddings0
Domain Adaptation of SRL Systems for Biological Processes0
Domain Adaptation of Synthetic Driving Datasets for Real-World Autonomous Driving0
Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback0
Domain Adaptation of VLM for Soccer Video Understanding0
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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