Domain Adaptation On Visda2017

Metrics

Accuracy

Results

Performance results of various models on this benchmark

		Paper Title	Repository
FFTAT	93.8	Feature Fusion Transferability Aware Transformer for Unsupervised Domain Adaptation
RCL	93.2	Empowering Source-Free Domain Adaptation via MLLM-Guided Reliability-Based Curriculum Learning
MIC	92.8	MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
SWG	92.7	Combining inherent knowledge of vision-language models with unsupervised domain adaptation through strong-weak guidance
CMKD	91.8	Unsupervised Domain Adaption Harnessing Vision-Language Pre-training	-
DePT	90.7	Visual Prompt Tuning for Test-time Domain Adaptation	-
SDAT(ViT)	89.8	A Closer Look at Smoothness in Domain Adversarial Training
SFDA2++	89.6	SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
PMtrans	88.8	Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective	-
CoVi	88.5	Contrastive Vicinal Space for Unsupervised Domain Adaptation
CDTrans	88.4	CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
SFDA2	88.1	SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
CAN	87.2	Contrastive Adaptation Network for Unsupervised Domain Adaptation
FixBi	87.2	FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation
dSNE	86.15	d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding	-
CPGA	86.0	Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation
Mean teacher	85.4	Self-ensembling for visual domain adaptation
MCC+NWD	83.7	Reusing the Task-specific Classifier as a Discriminator: Discriminator-free Adversarial Domain Adaptation
SHOT	82.9	Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
DTA	81.5	Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation

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Domain Adaptation On Visda2017

Metrics

Results