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SOTA
Adaptation de domaine
Domain Adaptation On Office 31
Domain Adaptation On Office 31
Métriques
Average Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
Average Accuracy
Paper Title
Repository
d-SNE
81.63
Supervised Domain Adaptation: A Graph Embedding Perspective and a Rectified Experimental Protocol
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DAOD
85.4
Open Set Domain Adaptation: Theoretical Bound and Algorithm
-
MRKLD + LRENT
86.8
Confidence Regularized Self-Training
-
CMKD
94.4
Unsupervised Domain Adaption Harnessing Vision-Language Pre-training
DADA
89
Discriminative Adversarial Domain Adaptation
-
GTA
86.5
Generate To Adapt: Aligning Domains using Generative Adversarial Networks
-
PMTrans
95.3
Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective
-
CAADA
78.3
Correlation-aware Adversarial Domain Adaptation and Generalization
-
rRevGrad+CAT
80.1
Cluster Alignment with a Teacher for Unsupervised Domain Adaptation
-
IDDA(Alexnet)
78.5
Looking back at Labels: A Class based Domain Adaptation Technique
-
SHOT
88.6
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
-
CDTrans
92.6
CDTrans: Cross-domain Transformer for Unsupervised Domain Adaptation
-
FixBi
91.4
FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation
-
BIWAA
90.5
Backprop Induced Feature Weighting for Adversarial Domain Adaptation with Iterative Label Distribution Alignment
SFDA2
89.9
SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
-
SRDA (RAN)
73.5
Learning Smooth Representation for Unsupervised Domain Adaptation
-
IDDA (AlexNet)
78.5
Looking back at Labels: A Class based Domain Adaptation Technique
-
dSNE
90.01
d-SNE: Domain Adaptation Using Stochastic Neighborhood Embedding
ELS
90.4
Free Lunch for Domain Adversarial Training: Environment Label Smoothing
-
ResNet-50
76.1
Deep Residual Learning for Image Recognition
-
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