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 13511400 of 6439 papers

TitleStatusHype
Diffusion-Driven Domain Adaptation for Generating 3D Molecules0
Diffusion Transport Alignment0
Angular Visual Hardness0
CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation0
Different Strokes for Different Folks: Investigating Appropriate Further Pre-training Approaches for Diverse Dialogue Tasks0
CA-UDA: Class-Aware Unsupervised Domain Adaptation with Optimal Assignment and Pseudo-Label Refinement0
ADeLA: Automatic Dense Labeling With Attention for Viewpoint Shift in Semantic Segmentation0
CATS: Mitigating Correlation Shift for Multivariate Time Series Classification0
An Exercise in Reuse of Resources: Adapting General Discourse Coreference Resolution for Detecting Lexical Chains in Patent Documentation0
Adversarial Transfer Learning for Cross-domain Visual Recognition0
CAT: Exploiting Inter-Class Dynamics for Domain Adaptive Object Detection0
AD-Aligning: Emulating Human-like Generalization for Cognitive Domain Adaptation in Deep Learning0
Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models0
A New Multiple Source Domain Adaptation Fault Diagnosis Method between Different Rotating Machines0
A Deep Fusion Model for Domain Adaptation in Phrase-based MT0
Cataract-1K: Cataract Surgery Dataset for Scene Segmentation, Phase Recognition, and Irregularity Detection0
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation0
Differentially Private Domain Adaptation with Theoretical Guarantees0
CASIA at SemEval-2022 Task 11: Chinese Named Entity Recognition for Complex and Ambiguous Entities0
Case-based Reasoning Augmented Large Language Model Framework for Decision Making in Realistic Safety-Critical Driving Scenarios0
A New Class of Efficient Adaptive Filters for Online Nonlinear Modeling0
Can We Teach Computers to Understand Art? Domain Adaptation for Enhancing Deep Networks Capacity to De-Abstract Art0
A New Bidirectional Unsupervised Domain Adaptation Segmentation Framework0
Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling0
Can We Evaluate Domain Adaptation Models Without Target-Domain Labels?0
cantnlp@LT-EDI-2024: Automatic Detection of Anti-LGBTQ+ Hate Speech in Under-resourced Languages0
Can Shadows Reveal Biometric Information?0
An Evaluation of Deep CNN Baselines for Scene-Independent Person Re-Identification0
AdaEmbed: Semi-supervised Domain Adaptation in the Embedding Space0
Can domain adaptation make object recognition work for everyone?0
Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation0
A Neural Network Model for Low-Resource Universal Dependency Parsing0
Can Domain Adaptation be Handled as Analogies?0
Understanding Behavior of Clinical Models under Domain Shifts0
Addressing Zero-Resource Domains Using Document-Level Context in Neural Machine Translation0
DiffClass: Diffusion-Based Class Incremental Learning0
Can Data Diversity Enhance Learning Generalization?0
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians0
Accurate Unsupervised Joint Named-Entity Extraction from Unaligned Parallel Text0
An Empirical Study on Measuring the Similarity of Sentential Arguments with Language Model Domain Adaptation0
Camera-Driven Representation Learning for Unsupervised Domain Adaptive Person Re-identification0
Addressing Slot-Value Changes in Task-oriented Dialogue Systems through Dialogue Domain Adaptation0
DIDA: Denoised Imitation Learning based on Domain Adaptation0
An Empirical Study of the Generalization Ability of Lidar 3D Object Detectors to Unseen Domains0
Revisiting Simple Domain Adaptation Methods in Unsupervised Neural Machine Translation0
CANU-ReID: A Conditional Adversarial Network for Unsupervised person Re-IDentification0
AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation0
DiDA: Disentangled Synthesis for Domain Adaptation0
Different Flavors of GUM: Evaluating Genre and Sentence Type Effects on Multilayer Corpus Annotation Quality0
Diffusion and Multi-Domain Adaptation Methods for Eosinophil 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