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Source Free Domain Adaptation On Visda 2017

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

		Paper Title
RCL	93.2	Empowering Source-Free Domain Adaptation via MLLM-Guided Reliability-Based Curriculum Learning
SFDA2++	89.6	SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
SFDA2	88.1	SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
C-SFDA	87.8	C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation
SHOT++	87.3	Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
DaC	87.3	Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning
NRC	85.9	Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation
G-SFDA	85.4	Generalized Source-free Domain Adaptation
SHOT	82.9	Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation

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Source Free Domain Adaptation On Visda 2017 | SOTA | HyperAI초신경