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Unknown Sample Discovery for Source Free Open Set Domain Adaptation

Unknown Sample Discovery for Source Free Open Set Domain Adaptation

5 December 2023
C. S. Jahan
Andreas E. Savakis
    TTA
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Papers citing "Unknown Sample Discovery for Source Free Open Set Domain Adaptation"

24 / 24 papers shown
Title
Attracting and Dispersing: A Simple Approach for Source-free Domain
  Adaptation
Attracting and Dispersing: A Simple Approach for Source-free Domain Adaptation
Shiqi Yang
Yaxing Wang
Kai Wang
Shangling Jui
Joost van de Weijer
62
139
0
09 May 2022
Selective-Supervised Contrastive Learning with Noisy Labels
Selective-Supervised Contrastive Learning with Noisy Labels
Shikun Li
Xiaobo Xia
Shiming Ge
Tongliang Liu
NoLa
63
176
0
08 Mar 2022
Progressively Select and Reject Pseudo-labelled Samples for Open-Set
  Domain Adaptation
Progressively Select and Reject Pseudo-labelled Samples for Open-Set Domain Adaptation
Qian Wang
Fanlin Meng
T. Breckon
VLM
BDL
53
21
0
25 Oct 2021
On the Effectiveness of Image Rotation for Open Set Domain Adaptation
On the Effectiveness of Image Rotation for Open Set Domain Adaptation
S. Bucci
Mohammad Reza Loghmani
Tatiana Tommasi
101
149
0
24 Jul 2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer
  for Unsupervised Domain Adaptation
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Jian Liang
Dapeng Hu
Jiashi Feng
95
1,238
0
20 Feb 2020
Universal Domain Adaptation through Self Supervision
Universal Domain Adaptation through Self Supervision
Kuniaki Saito
Donghyun Kim
Stan Sclaroff
Kate Saenko
OOD
TTA
77
320
0
19 Feb 2020
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
DivideMix: Learning with Noisy Labels as Semi-supervised Learning
Junnan Li
R. Socher
Guosheng Lin
NoLa
94
1,026
0
18 Feb 2020
Open Set Domain Adaptation: Theoretical Bound and Algorithm
Open Set Domain Adaptation: Theoretical Bound and Algorithm
Zhen Fang
Jie Lu
Feng Liu
Junyu Xuan
Guangquan Zhang
45
153
0
19 Jul 2019
When Does Label Smoothing Help?
When Does Label Smoothing Help?
Rafael Müller
Simon Kornblith
Geoffrey E. Hinton
UQCV
175
1,938
0
06 Jun 2019
Unsupervised Label Noise Modeling and Loss Correction
Unsupervised Label Noise Modeling and Loss Correction
Eric Arazo Sanchez
Diego Ortego
Paul Albert
Noel E. O'Connor
Kevin McGuinness
NoLa
74
610
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
81
344
0
25 Apr 2019
Open Set Domain Adaptation by Backpropagation
Open Set Domain Adaptation by Backpropagation
Kuniaki Saito
Shohei Yamamoto
Yoshitaka Ushiku
Tatsuya Harada
VLM
74
505
0
27 Apr 2018
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
CyCADA: Cycle-Consistent Adversarial Domain Adaptation
Judy Hoffman
Eric Tzeng
Taesung Park
Jun-Yan Zhu
Phillip Isola
Kate Saenko
Alexei A. Efros
Trevor Darrell
134
3,001
0
08 Nov 2017
Deep Hashing Network for Unsupervised Domain Adaptation
Deep Hashing Network for Unsupervised Domain Adaptation
Hemanth Venkateswara
José Eusébio
Shayok Chakraborty
S. Panchanathan
OOD
138
2,041
0
22 Jun 2017
Adversarial Discriminative Domain Adaptation
Adversarial Discriminative Domain Adaptation
Eric Tzeng
Judy Hoffman
Kate Saenko
Trevor Darrell
GAN
OOD
257
4,655
0
17 Feb 2017
Temporal Ensembling for Semi-Supervised Learning
Temporal Ensembling for Semi-Supervised Learning
S. Laine
Timo Aila
UQCV
181
2,552
0
07 Oct 2016
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Deep CORAL: Correlation Alignment for Deep Domain Adaptation
Baochen Sun
Kate Saenko
OOD
97
3,144
0
06 Jul 2016
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
366
9,467
0
28 May 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
340
13,123
0
12 Mar 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
428
43,234
0
11 Feb 2015
Learning Transferable Features with Deep Adaptation Networks
Learning Transferable Features with Deep Adaptation Networks
Mingsheng Long
Yue Cao
Jianmin Wang
Michael I. Jordan
OOD
215
5,189
0
10 Feb 2015
Deep Domain Confusion: Maximizing for Domain Invariance
Deep Domain Confusion: Maximizing for Domain Invariance
Eric Tzeng
Judy Hoffman
Ning Zhang
Kate Saenko
Trevor Darrell
OOD
167
2,598
0
10 Dec 2014
Microsoft COCO: Common Objects in Context
Microsoft COCO: Common Objects in Context
Nayeon Lee
Michael Maire
Serge J. Belongie
Lubomir Bourdev
Ross B. Girshick
James Hays
Pietro Perona
Deva Ramanan
C. L. Zitnick
Piotr Dollár
ObjD
377
43,524
0
01 May 2014
Information-Theoretical Learning of Discriminative Clusters for
  Unsupervised Domain Adaptation
Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation
Yuan Shi
Fei Sha
109
243
0
27 Jun 2012
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