HyperAI초신경

홈 뉴스 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

한국어

HyperAI초신경

Source Free Domain Adaptation On Visda 2017

평가 지표

Accuracy

평가 결과

이 벤치마크에서 각 모델의 성능 결과

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

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