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When Does Contrastive Visual Representation Learning Work?
v1v2 (latest)

When Does Contrastive Visual Representation Learning Work?

12 May 2021
Elijah Cole
Xuan S. Yang
Kimberly Wilber
Oisin Mac Aodha
Serge Belongie
    SSL
ArXiv (abs)PDFHTML

Papers citing "When Does Contrastive Visual Representation Learning Work?"

50 / 61 papers shown
Title
Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures
Kun Yuan
V. Srivastav
Tong Yu
Joël L. Lavanchy
J. Marescaux
Pietro Mascagni
Nassir Navab
N. Padoy
126
23
0
27 Jul 2023
Vision Models Are More Robust And Fair When Pretrained On Uncurated
  Images Without Supervision
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision
Priya Goyal
Quentin Duval
Isaac Seessel
Mathilde Caron
Ishan Misra
Levent Sagun
Armand Joulin
Piotr Bojanowski
VLMSSL
87
111
0
16 Feb 2022
ResNet strikes back: An improved training procedure in timm
ResNet strikes back: An improved training procedure in timm
Ross Wightman
Hugo Touvron
Hervé Jégou
AI4TS
263
498
0
01 Oct 2021
Early Convolutions Help Transformers See Better
Early Convolutions Help Transformers See Better
Tete Xiao
Mannat Singh
Eric Mintun
Trevor Darrell
Piotr Dollár
Ross B. Girshick
55
771
0
28 Jun 2021
Revisiting Contrastive Methods for Unsupervised Learning of Visual
  Representations
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
Wouter Van Gansbeke
Simon Vandenhende
Stamatios Georgoulis
Luc Van Gool
SSL
106
65
0
10 Jun 2021
Divide and Contrast: Self-supervised Learning from Uncurated Data
Divide and Contrast: Self-supervised Learning from Uncurated Data
Yonglong Tian
Olivier J. Hénaff
Aaron van den Oord
SSL
115
101
0
17 May 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
708
6,127
0
29 Apr 2021
Benchmarking Representation Learning for Natural World Image Collections
Benchmarking Representation Learning for Natural World Image Collections
Grant Van Horn
Elijah Cole
Sara Beery
Kimberly Wilber
Serge J. Belongie
Oisin Mac Aodha
SSLVLM
74
177
0
30 Mar 2021
Contrasting Contrastive Self-Supervised Representation Learning
  Pipelines
Contrasting Contrastive Self-Supervised Representation Learning Pipelines
Klemen Kotar
Gabriel Ilharco
Ludwig Schmidt
Kiana Ehsani
Roozbeh Mottaghi
SSL
86
46
0
25 Mar 2021
Efficient Visual Pretraining with Contrastive Detection
Efficient Visual Pretraining with Contrastive Detection
Olivier J. Hénaff
Skanda Koppula
Jean-Baptiste Alayrac
Aaron van den Oord
Oriol Vinyals
João Carreira
VLMSSL
71
165
0
19 Mar 2021
Self-supervised Pretraining of Visual Features in the Wild
Self-supervised Pretraining of Visual Features in the Wild
Priya Goyal
Mathilde Caron
Benjamin Lefaudeux
Min Xu
Pengchao Wang
...
Mannat Singh
Vitaliy Liptchinsky
Ishan Misra
Armand Joulin
Piotr Bojanowski
VLMSSL
76
274
0
02 Mar 2021
Exploring Cross-Image Pixel Contrast for Semantic Segmentation
Exploring Cross-Image Pixel Contrast for Semantic Segmentation
Wenguan Wang
Tianfei Zhou
Feng Yu
Jifeng Dai
E. Konukoglu
Luc Van Gool
196
481
0
28 Jan 2021
Concept Generalization in Visual Representation Learning
Concept Generalization in Visual Representation Learning
Mert Bulent Sariyildiz
Yannis Kalantidis
Diane Larlus
Alahari Karteek
SSL
100
50
0
10 Dec 2020
How Well Do Self-Supervised Models Transfer?
How Well Do Self-Supervised Models Transfer?
Linus Ericsson
Henry Gouk
Timothy M. Hospedales
SSL
114
278
0
26 Nov 2020
Exploring Simple Siamese Representation Learning
Exploring Simple Siamese Representation Learning
Xinlei Chen
Kaiming He
SSL
258
4,072
0
20 Nov 2020
Geography-Aware Self-Supervised Learning
Geography-Aware Self-Supervised Learning
Kumar Ayush
Burak Uzkent
Chenlin Meng
Kumar Tanmay
Marshall Burke
David B. Lobell
Stefano Ermon
SSL
80
235
0
19 Nov 2020
Intriguing Properties of Contrastive Losses
Intriguing Properties of Contrastive Losses
Ting Chen
Calvin Luo
Lala Li
72
177
0
05 Nov 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at
  Scale
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Alexey Dosovitskiy
Lucas Beyer
Alexander Kolesnikov
Dirk Weissenborn
Xiaohua Zhai
...
Matthias Minderer
G. Heigold
Sylvain Gelly
Jakob Uszkoreit
N. Houlsby
ViT
670
41,430
0
22 Oct 2020
Contrastive Learning of General-Purpose Audio Representations
Contrastive Learning of General-Purpose Audio Representations
Aaqib Saeed
David Grangier
Neil Zeghidour
VLMSSL
76
272
0
21 Oct 2020
Data Valuation for Medical Imaging Using Shapley Value: Application on A
  Large-scale Chest X-ray Dataset
Data Valuation for Medical Imaging Using Shapley Value: Application on A Large-scale Chest X-ray Dataset
Siyi Tang
Amirata Ghorbani
R. Yamashita
Sameer Rehman
Jared A. Dunnmon
James Zou
D. Rubin
TDI
46
81
0
15 Oct 2020
Self-Supervised Ranking for Representation Learning
Self-Supervised Ranking for Representation Learning
Ali Varamesh
Ali Diba
Tinne Tuytelaars
Luc Van Gool
SSLAI4TS
53
9
0
14 Oct 2020
Are all negatives created equal in contrastive instance discrimination?
Are all negatives created equal in contrastive instance discrimination?
Tiffany Cai
Jonathan Frankle
D. Schwab
Ari S. Morcos
SSL
67
83
0
13 Oct 2020
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability
  of Chest X-ray Models
MoCo-CXR: MoCo Pretraining Improves Representation and Transferability of Chest X-ray Models
Hari Sowrirajan
Jingbo Yang
A. Ng
Pranav Rajpurkar
92
86
0
11 Oct 2020
EqCo: Equivalent Rules for Self-supervised Contrastive Learning
EqCo: Equivalent Rules for Self-supervised Contrastive Learning
Benjin Zhu
Junqiang Huang
Zeming Li
Xiangyu Zhang
Jian Sun
SSL
63
13
0
05 Oct 2020
Data-Efficient Pretraining via Contrastive Self-Supervision
Data-Efficient Pretraining via Contrastive Self-Supervision
Nils Rethmeier
Isabelle Augenstein
69
21
0
02 Oct 2020
What Should Not Be Contrastive in Contrastive Learning
What Should Not Be Contrastive in Contrastive Learning
Tete Xiao
Xiaolong Wang
Alexei A. Efros
Trevor Darrell
SSLDRL
82
303
0
13 Aug 2020
Demystifying Contrastive Self-Supervised Learning: Invariances,
  Augmentations and Dataset Biases
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases
Senthil Purushwalkam
Abhinav Gupta
SSL
79
219
0
28 Jul 2020
Parametric Instance Classification for Unsupervised Visual Feature
  Learning
Parametric Instance Classification for Unsupervised Visual Feature Learning
Yue Cao
Zhenda Xie
B. Liu
Yutong Lin
Zheng Zhang
Han Hu
VLM
71
61
0
25 Jun 2020
Transfer Learning or Self-supervised Learning? A Tale of Two Pretraining
  Paradigms
Transfer Learning or Self-supervised Learning? A Tale of Two Pretraining Paradigms
Xingyi Yang
Xuehai He
Yuxiao Liang
Yue Yang
Shanghang Zhang
P. Xie
SSL
63
43
0
19 Jun 2020
Unsupervised Learning of Visual Features by Contrasting Cluster
  Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
261
4,098
0
17 Jun 2020
Bootstrap your own latent: A new approach to self-supervised Learning
Bootstrap your own latent: A new approach to self-supervised Learning
Jean-Bastien Grill
Florian Strub
Florent Altché
Corentin Tallec
Pierre Harvey Richemond
...
M. G. Azar
Bilal Piot
Koray Kavukcuoglu
Rémi Munos
Michal Valko
SSL
395
6,837
0
13 Jun 2020
Rethinking Pre-training and Self-training
Rethinking Pre-training and Self-training
Barret Zoph
Golnaz Ghiasi
Nayeon Lee
Huayu Chen
Hanxiao Liu
E. D. Cubuk
Quoc V. Le
SSeg
101
652
0
11 Jun 2020
VirTex: Learning Visual Representations from Textual Annotations
VirTex: Learning Visual Representations from Textual Annotations
Karan Desai
Justin Johnson
SSLVLM
160
436
0
11 Jun 2020
What makes instance discrimination good for transfer learning?
What makes instance discrimination good for transfer learning?
Nanxuan Zhao
Zhirong Wu
Rynson W. H. Lau
Stephen Lin
SSL
74
170
0
11 Jun 2020
Supervised Contrastive Learning
Supervised Contrastive Learning
Prannay Khosla
Piotr Teterwak
Chen Wang
Aaron Sarna
Yonglong Tian
Phillip Isola
Aaron Maschinot
Ce Liu
Dilip Krishnan
SSL
165
4,572
0
23 Apr 2020
The GeoLifeCLEF 2020 Dataset
The GeoLifeCLEF 2020 Dataset
Elijah Cole
Benjamin Deneu
Titouan Lorieul
Maximilien Servajean
Christophe Botella
Dan Morris
Nebojsa Jojic
P. Bonnet
Alexis Joly
26
23
0
08 Apr 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
492
3,443
0
09 Mar 2020
A Simple Framework for Contrastive Learning of Visual Representations
A Simple Framework for Contrastive Learning of Visual Representations
Ting-Li Chen
Simon Kornblith
Mohammad Norouzi
Geoffrey E. Hinton
SSL
378
18,866
0
13 Feb 2020
Measuring Dataset Granularity
Measuring Dataset Granularity
Huayu Chen
Zeqi Gu
D. Mahajan
Laurens van der Maaten
Serge J. Belongie
Ser-Nam Lim
67
13
0
21 Dec 2019
Momentum Contrast for Unsupervised Visual Representation Learning
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He
Haoqi Fan
Yuxin Wu
Saining Xie
Ross B. Girshick
SSL
213
12,124
0
13 Nov 2019
Fixing the train-test resolution discrepancy
Fixing the train-test resolution discrepancy
Hugo Touvron
Andrea Vedaldi
Matthijs Douze
Hervé Jégou
127
423
0
14 Jun 2019
Contrastive Multiview Coding
Contrastive Multiview Coding
Yonglong Tian
Dilip Krishnan
Phillip Isola
SSL
174
2,409
0
13 Jun 2019
Data-Efficient Image Recognition with Contrastive Predictive Coding
Data-Efficient Image Recognition with Contrastive Predictive Coding
Olivier J. Hénaff
A. Srinivas
J. Fauw
Ali Razavi
Carl Doersch
S. M. Ali Eslami
Aaron van den Oord
SSL
138
1,432
0
22 May 2019
Scaling and Benchmarking Self-Supervised Visual Representation Learning
Scaling and Benchmarking Self-Supervised Visual Representation Learning
Priya Goyal
D. Mahajan
Abhinav Gupta
Ishan Misra
SSL
75
397
0
03 May 2019
ImageNet-trained CNNs are biased towards texture; increasing shape bias
  improves accuracy and robustness
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness
Robert Geirhos
Patricia Rubisch
Claudio Michaelis
Matthias Bethge
Felix Wichmann
Wieland Brendel
124
2,673
0
29 Nov 2018
Recognition in Terra Incognita
Recognition in Terra Incognita
Sara Beery
Grant Van Horn
Pietro Perona
97
852
0
13 Jul 2018
Representation Learning with Contrastive Predictive Coding
Representation Learning with Contrastive Predictive Coding
Aaron van den Oord
Yazhe Li
Oriol Vinyals
DRLSSL
351
10,356
0
10 Jul 2018
Exploring the Limits of Weakly Supervised Pretraining
Exploring the Limits of Weakly Supervised Pretraining
D. Mahajan
Ross B. Girshick
Vignesh Ramanathan
Kaiming He
Manohar Paluri
Yixuan Li
Ashwin R. Bharambe
Laurens van der Maaten
VLM
199
1,370
0
02 May 2018
Unsupervised Representation Learning by Predicting Image Rotations
Unsupervised Representation Learning by Predicting Image Rotations
Spyros Gidaris
Praveer Singh
N. Komodakis
OODSSLDRL
264
3,298
0
21 Mar 2018
Critical Learning Periods in Deep Neural Networks
Critical Learning Periods in Deep Neural Networks
Alessandro Achille
Matteo Rovere
Stefano Soatto
60
99
0
24 Nov 2017
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