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SVHN-to-MNIST
Domain Adaptation on SVHN-to-MNIST
Metric: Accuracy (higher is better)
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Model name (A→Z)
#
Model
↕
Accuracy
▼
Augmentations
Paper
Date
↕
Code
1
Mean teacher
99.18
No
Self-ensembling for visual domain adaptation
2017-06-16
Code
2
SHOT
98.9
No
Do We Really Need to Access the Source Data? Sou...
2020-02-20
Code
3
DFA-MCD
98.9
No
Discriminative Feature Alignment: Improving Tran...
2020-06-23
Code
4
FAMCD
98.76
No
-
-
-
5
DFA-ENT
98.2
No
Discriminative Feature Alignment: Improving Tran...
2020-06-23
Code
6
CyCleGAN (Light-weight Calibrator)
97.5
No
Light-weight Calibrator: a Separable Component f...
2019-11-28
Code
7
MCD
95.8
No
Maximum Classifier Discrepancy for Unsupervised ...
2017-12-07
Code
8
PFA
93.9
No
Progressive Feature Alignment for Unsupervised D...
2018-11-21
-
9
MSTN
93.3
No
-
-
Code
10
FACT
90.6
No
FACT: Federated Adversarial Cross Training
2023-06-01
Code
11
CYCADA
90.4
No
CyCADA: Cycle-Consistent Adversarial Domain Adap...
2017-11-08
Code
12
CDAN
89.2
No
Conditional Adversarial Domain Adaptation
2017-05-26
Code
13
ADDN
80.1
No
Adversarial Discriminative Domain Adaptation
2017-02-17
Code
14
SBADA
76.1
No
From source to target and back: symmetric bi-dir...
2017-05-24
-
#1
Mean teacher
SOTA
99.18
Accuracy
· 2017-06-16
Self-ensembling for visual domain adaptation
Code
#2
SHOT
98.9
Accuracy
· 2020-02-20
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Code
#3
DFA-MCD
98.9
Accuracy
· 2020-06-23
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
Code
#4
FAMCD
98.76
Accuracy
No paper
#5
DFA-ENT
98.2
Accuracy
· 2020-06-23
Discriminative Feature Alignment: Improving Transferability of Unsupervised Domain Adaptation by Gaussian-guided Latent Alignment
Code
#6
CyCleGAN (Light-weight Calibrator)
97.5
Accuracy
· 2019-11-28
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation
Code
#7
MCD
95.8
Accuracy
· 2017-12-07
Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
Code
#8
PFA
93.9
Accuracy
· 2018-11-21
Progressive Feature Alignment for Unsupervised Domain Adaptation
#9
MSTN
93.3
Accuracy
No paper
Code
#10
FACT
90.6
Accuracy
· 2023-06-01
FACT: Federated Adversarial Cross Training
Code
#11
CYCADA
90.4
Accuracy
· 2017-11-08
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Code
#12
CDAN
SOTA
89.2
Accuracy
· 2017-05-26
Conditional Adversarial Domain Adaptation
Code
#13
ADDN
SOTA
80.1
Accuracy
· 2017-02-17
Adversarial Discriminative Domain Adaptation
Code
#14
SBADA
76.1
Accuracy
· 2017-05-24
From source to target and back: symmetric bi-directional adaptive GAN