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Source Free Domain Adaptation On Visda 2017

Metrics

Accuracy

Results

Performance results of various models on this benchmark

Model Name
Accuracy
Paper TitleRepository
SFDA2++89.6SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
RCL93.2Empowering Source-Free Domain Adaptation with MLLM-driven Curriculum Learning
NRC85.9Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation
G-SFDA85.4Generalized Source-free Domain Adaptation
SHOT++87.3Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
SHOT82.9Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
SFDA288.1SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
DaC87.3Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning
C-SFDA87.8C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation
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