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Unsupervised Few-shot Learning via Self-supervised Training

Unsupervised Few-shot Learning via Self-supervised Training

20 December 2019
Zilong Ji
Xiaolong Zou
Tiejun Huang
Si Wu
    SSL
ArXiv (abs)PDFHTML

Papers citing "Unsupervised Few-shot Learning via Self-supervised Training"

22 / 22 papers shown
Title
Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via
  Random Labels and Data Augmentation
Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation
Antreas Antoniou
Amos Storkey
SSL
70
75
0
26 Feb 2019
Unsupervised Learning via Meta-Learning
Unsupervised Learning via Meta-Learning
Kyle Hsu
Sergey Levine
Chelsea Finn
SSLOffRL
79
230
0
04 Oct 2018
Unsupervised Domain Adaptive Re-Identification: Theory and Practice
Unsupervised Domain Adaptive Re-Identification: Theory and Practice
Liangchen Song
Cheng Wang
Lefei Zhang
Bo Du
Qian Zhang
Chang Huang
Xinggang Wang
OOD
60
346
0
30 Jul 2018
Towards Good Practices on Building Effective CNN Baseline Model for
  Person Re-identification
Towards Good Practices on Building Effective CNN Baseline Model for Person Re-identification
Fu Xiong
Yang Xiao
Zhiguo Cao
Kaicheng Gong
Zhiwen Fang
Qiufeng Wang
CVBM
44
50
0
29 Jul 2018
Meta-Learning with Latent Embedding Optimization
Meta-Learning with Latent Embedding Optimization
Andrei A. Rusu
Dushyant Rao
Jakub Sygnowski
Oriol Vinyals
Razvan Pascanu
Simon Osindero
R. Hadsell
139
1,371
0
16 Jul 2018
Deep Clustering for Unsupervised Learning of Visual Features
Deep Clustering for Unsupervised Learning of Visual Features
Mathilde Caron
Piotr Bojanowski
Armand Joulin
Matthijs Douze
SSL
88
1,898
0
15 Jul 2018
Attention-based Few-Shot Person Re-identification Using Meta Learning
Attention-based Few-Shot Person Re-identification Using Meta Learning
Alireza Rahimpour
Hairong Qi
41
5
0
24 Jun 2018
Learning to Propagate Labels: Transductive Propagation Network for
  Few-shot Learning
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu
Juho Lee
Minseop Park
Saehoon Kim
Eunho Yang
Sung Ju Hwang
Yi Yang
98
668
0
25 May 2018
On First-Order Meta-Learning Algorithms
On First-Order Meta-Learning Algorithms
Alex Nichol
Joshua Achiam
John Schulman
230
2,232
0
08 Mar 2018
Meta-Learning for Semi-Supervised Few-Shot Classification
Meta-Learning for Semi-Supervised Few-Shot Classification
Mengye Ren
Eleni Triantafillou
S. S. Ravi
Jake C. Snell
Kevin Swersky
J. Tenenbaum
Hugo Larochelle
R. Zemel
SSL
70
1,283
0
02 Mar 2018
Low-Shot Learning from Imaginary Data
Low-Shot Learning from Imaginary Data
Yu-Xiong Wang
Ross B. Girshick
M. Hebert
Bharath Hariharan
VLM
97
677
0
16 Jan 2018
Learning to Compare: Relation Network for Few-Shot Learning
Learning to Compare: Relation Network for Few-Shot Learning
Flood Sung
Yongxin Yang
Li Zhang
Tao Xiang
Philip Torr
Timothy M. Hospedales
295
4,050
0
16 Nov 2017
A Simple Neural Attentive Meta-Learner
A Simple Neural Attentive Meta-Learner
Nikhil Mishra
Mostafa Rohaninejad
Xi Chen
Pieter Abbeel
OOD
71
199
0
11 Jul 2017
Unsupervised Person Re-identification: Clustering and Fine-tuning
Unsupervised Person Re-identification: Clustering and Fine-tuning
Hehe Fan
Liang Zheng
Yi Yang
SSL
105
492
0
30 May 2017
In Defense of the Triplet Loss for Person Re-Identification
In Defense of the Triplet Loss for Person Re-Identification
Alexander Hermans
Lucas Beyer
Bastian Leibe
DML
78
3,206
0
22 Mar 2017
Prototypical Networks for Few-shot Learning
Prototypical Networks for Few-shot Learning
Jake C. Snell
Kevin Swersky
R. Zemel
300
8,134
0
15 Mar 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
823
11,909
0
09 Mar 2017
Re-ranking Person Re-identification with k-reciprocal Encoding
Re-ranking Person Re-identification with k-reciprocal Encoding
Zhun Zhong
Liang Zheng
Donglin Cao
Shaozi Li
129
1,504
0
29 Jan 2017
Cognitive Science in the era of Artificial Intelligence: A roadmap for
  reverse-engineering the infant language-learner
Cognitive Science in the era of Artificial Intelligence: A roadmap for reverse-engineering the infant language-learner
Emmanuel Dupoux
66
158
0
29 Jul 2016
Learning to learn by gradient descent by gradient descent
Learning to learn by gradient descent by gradient descent
Marcin Andrychowicz
Misha Denil
Sergio Gomez Colmenarejo
Matthew W. Hoffman
David Pfau
Tom Schaul
Brendan Shillingford
Nando de Freitas
110
2,006
0
14 Jun 2016
Matching Networks for One Shot Learning
Matching Networks for One Shot Learning
Oriol Vinyals
Charles Blundell
Timothy Lillicrap
Koray Kavukcuoglu
Daan Wierstra
VLM
373
7,323
0
13 Jun 2016
Unsupervised Deep Embedding for Clustering Analysis
Unsupervised Deep Embedding for Clustering Analysis
Junyuan Xie
Ross B. Girshick
Ali Farhadi
SSL
86
2,875
0
19 Nov 2015
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