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Self-ensembling for visual domain adaptation

Self-ensembling for visual domain adaptation

16 June 2017
Geoffrey French
Michal Mackiewicz
M. Fisher
ArXivPDFHTML

Papers citing "Self-ensembling for visual domain adaptation"

26 / 26 papers shown
Title
Say No to Freeloader: Protecting Intellectual Property of Your Deep
  Model
Say No to Freeloader: Protecting Intellectual Property of Your Deep Model
Lianyu Wang
Hao Wu
Huazhu Fu
Daoqiang Zhang
42
2
0
23 Aug 2024
S4DL: Shift-sensitive Spatial-Spectral Disentangling Learning for
  Hyperspectral Image Unsupervised Domain Adaptation
S4DL: Shift-sensitive Spatial-Spectral Disentangling Learning for Hyperspectral Image Unsupervised Domain Adaptation
Jie Feng
Tianshu Zhang
Junpeng Zhang
Ronghua Shang
Weisheng Dong
G. Shi
Licheng Jiao
29
2
0
11 Aug 2024
Source-Free Domain Adaptation Guided by Vision and Vision-Language
  Pre-Training
Source-Free Domain Adaptation Guided by Vision and Vision-Language Pre-Training
Wenyu Zhang
Li Shen
Chuan-Sheng Foo
VLM
TTA
42
4
0
05 May 2024
Model Barrier: A Compact Un-Transferable Isolation Domain for Model
  Intellectual Property Protection
Model Barrier: A Compact Un-Transferable Isolation Domain for Model Intellectual Property Protection
Lianyu Wang
Meng Wang
Daoqiang Zhang
Huazhu Fu
26
18
0
20 Mar 2023
Rethinking the Role of Pre-Trained Networks in Source-Free Domain
  Adaptation
Rethinking the Role of Pre-Trained Networks in Source-Free Domain Adaptation
Wenyu Zhang
Li Shen
Chuan-Sheng Foo
TTA
AI4CE
34
15
0
15 Dec 2022
Transferability in Deep Learning: A Survey
Transferability in Deep Learning: A Survey
Junguang Jiang
Yang Shu
Jianmin Wang
Mingsheng Long
OOD
34
101
0
15 Jan 2022
Transferrable Contrastive Learning for Visual Domain Adaptation
Transferrable Contrastive Learning for Visual Domain Adaptation
Yang Chen
Yingwei Pan
Yu Wang
Ting Yao
Xinmei Tian
Tao Mei
19
23
0
14 Dec 2021
Non-Transferable Learning: A New Approach for Model Ownership
  Verification and Applicability Authorization
Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization
Lixu Wang
Shichao Xu
Ruiqi Xu
Tianlin Li
Qi Zhu
AAML
19
45
0
13 Jun 2021
Online Domain Adaptation for Continuous Cross-Subject Liver Viability
  Evaluation Based on Irregular Thermal Data
Online Domain Adaptation for Continuous Cross-Subject Liver Viability Evaluation Based on Irregular Thermal Data
Sahand Hajifar
Hongyue Sun
18
7
0
24 Nov 2020
Learning a Domain Classifier Bank for Unsupervised Adaptive Object
  Detection
Learning a Domain Classifier Bank for Unsupervised Adaptive Object Detection
Sanli Tang
Zhanzhan Cheng
Shiliang Pu
Dashan Guo
Yi Niu
Fei Wu
8
2
0
06 Jul 2020
Improving robustness against common corruptions by covariate shift
  adaptation
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider
E. Rusak
L. Eck
Oliver Bringmann
Wieland Brendel
Matthias Bethge
VLM
42
458
0
30 Jun 2020
Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation
Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation
Yingwei Pan
Ting Yao
Yehao Li
Chong-Wah Ngo
Tao Mei
33
72
0
11 Jun 2020
Improving Unsupervised Domain Adaptation with Variational Information
  Bottleneck
Improving Unsupervised Domain Adaptation with Variational Information Bottleneck
Yuxuan Song
Lantao Yu
Zhangjie Cao
Zhiming Zhou
Jian Shen
Shuo Shao
Weinan Zhang
Yong Yu
31
17
0
21 Nov 2019
Unsupervised Domain Adaptation through Self-Supervision
Unsupervised Domain Adaptation through Self-Supervision
Yu Sun
Eric Tzeng
Trevor Darrell
Alexei A. Efros
OOD
SSL
21
236
0
26 Sep 2019
Contrastively Smoothed Class Alignment for Unsupervised Domain
  Adaptation
Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation
Shuyang Dai
Yu Cheng
Yizhe Zhang
Zhe Gan
Jingjing Liu
Lawrence Carin
13
27
0
11 Sep 2019
Dual Student: Breaking the Limits of the Teacher in Semi-supervised
  Learning
Dual Student: Breaking the Limits of the Teacher in Semi-supervised Learning
Zhanghan Ke
Daoye Wang
Qiong Yan
Jimmy S. J. Ren
Rynson W. H. Lau
11
212
0
03 Sep 2019
Exploring Object Relation in Mean Teacher for Cross-Domain Detection
Exploring Object Relation in Mean Teacher for Cross-Domain Detection
Qi Cai
Yingwei Pan
Chong-Wah Ngo
Xinmei Tian
Ling-yu Duan
Ting Yao
ViT
OOD
30
306
0
25 Apr 2019
Transferrable Prototypical Networks for Unsupervised Domain Adaptation
Transferrable Prototypical Networks for Unsupervised Domain Adaptation
Yingwei Pan
Ting Yao
Yehao Li
Yu Wang
Chong-Wah Ngo
Tao Mei
38
338
0
25 Apr 2019
Contrastive Adaptation Network for Unsupervised Domain Adaptation
Contrastive Adaptation Network for Unsupervised Domain Adaptation
Guoliang Kang
Lu Jiang
Yi Yang
Alexander G. Hauptmann
14
826
0
04 Jan 2019
Adversarial Domain Randomization
Adversarial Domain Randomization
Rawal Khirodkar
Kris M. Kitani
11
5
0
03 Dec 2018
Co-regularized Alignment for Unsupervised Domain Adaptation
Co-regularized Alignment for Unsupervised Domain Adaptation
Abhishek Kumar
P. Sattigeri
Kahini Wadhawan
Leonid Karlinsky
Rogerio Feris
William T. Freeman
G. Wornell
OOD
14
157
0
13 Nov 2018
Deep semi-supervised segmentation with weight-averaged consistency
  targets
Deep semi-supervised segmentation with weight-averaged consistency targets
C. Perone
Julien Cohen-Adad
OOD
14
72
0
12 Jul 2018
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation
Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation
Xingchao Peng
Ben Usman
Kuniaki Saito
Neela Kaushik
Judy Hoffman
Kate Saenko
18
75
0
26 Jun 2018
A DIRT-T Approach to Unsupervised Domain Adaptation
A DIRT-T Approach to Unsupervised Domain Adaptation
Rui Shu
Hung Bui
Hirokazu Narui
Stefano Ermon
27
610
0
23 Feb 2018
VisDA: The Visual Domain Adaptation Challenge
VisDA: The Visual Domain Adaptation Challenge
Xingchao Peng
Ben Usman
Neela Kaushik
Judy Hoffman
Dequan Wang
Kate Saenko
OOD
28
786
0
18 Oct 2017
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
264
1,275
0
06 Mar 2017
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