ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.11398
  4. Cited By
Why Do Self-Supervised Models Transfer? Investigating the Impact of
  Invariance on Downstream Tasks
v1v2 (latest)

Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks

22 November 2021
Linus Ericsson
Henry Gouk
Timothy M. Hospedales
    SSL
ArXiv (abs)PDFHTML

Papers citing "Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream Tasks"

30 / 30 papers shown
Title
Improving Transferability of Representations via Augmentation-Aware
  Self-Supervision
Improving Transferability of Representations via Augmentation-Aware Self-Supervision
Hankook Lee
Kibok Lee
Kimin Lee
Honglak Lee
Jinwoo Shin
SSL
61
55
0
18 Nov 2021
Self-Supervised Representation Learning: Introduction, Advances and
  Challenges
Self-Supervised Representation Learning: Introduction, Advances and Challenges
Linus Ericsson
Henry Gouk
Chen Change Loy
Timothy M. Hospedales
SSLOODAI4TS
79
278
0
18 Oct 2021
Self-Supervised Learning with Data Augmentations Provably Isolates
  Content from Style
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
Julius von Kügelgen
Yash Sharma
Luigi Gresele
Wieland Brendel
Bernhard Schölkopf
M. Besserve
Francesco Locatello
99
317
0
08 Jun 2021
Toward Understanding the Feature Learning Process of Self-supervised
  Contrastive Learning
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen
Yuanzhi Li
SSLMLT
74
136
0
31 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
713
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
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Barlow Twins: Self-Supervised Learning via Redundancy Reduction
Jure Zbontar
Li Jing
Ishan Misra
Yann LeCun
Stéphane Deny
SSL
347
2,362
0
04 Mar 2021
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
Learning Translation Invariance in CNNs
Learning Translation Invariance in CNNs
Valerio Biscione
J. Bowers
SSL
41
13
0
06 Nov 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
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
398
6,837
0
13 Jun 2020
Understanding Contrastive Representation Learning through Alignment and
  Uniformity on the Hypersphere
Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere
Tongzhou Wang
Phillip Isola
SSL
162
1,855
0
20 May 2020
Ventral-Dorsal Neural Networks: Object Detection via Selective Attention
Ventral-Dorsal Neural Networks: Object Detection via Selective Attention
M. K. Ebrahimpour
Jiayun Li
Yen-Yun Yu
Jackson Reesee
Azadeh Moghtaderi
Ming-Hsuan Yang
D. Noelle
ObjD
42
20
0
15 May 2020
Prototypical Contrastive Learning of Unsupervised Representations
Prototypical Contrastive Learning of Unsupervised Representations
Junnan Li
Pan Zhou
Caiming Xiong
Guosheng Lin
SSLDRL
139
975
0
11 May 2020
On Translation Invariance in CNNs: Convolutional Layers can Exploit
  Absolute Spatial Location
On Translation Invariance in CNNs: Convolutional Layers can Exploit Absolute Spatial Location
O. Kayhan
Jan van Gemert
313
236
0
16 Mar 2020
Improved Baselines with Momentum Contrastive Learning
Improved Baselines with Momentum Contrastive Learning
Xinlei Chen
Haoqi Fan
Ross B. Girshick
Kaiming He
SSL
495
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
381
18,866
0
13 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
544
42,591
0
03 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
RandAugment: Practical automated data augmentation with a reduced search
  space
RandAugment: Practical automated data augmentation with a reduced search space
E. D. Cubuk
Barret Zoph
Jonathon Shlens
Quoc V. Le
MQ
258
3,502
0
30 Sep 2019
Self-supervised Visual Feature Learning with Deep Neural Networks: A
  Survey
Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey
Longlong Jing
Yingli Tian
SSL
165
1,700
0
16 Feb 2019
AutoAugment: Learning Augmentation Policies from Data
AutoAugment: Learning Augmentation Policies from Data
E. D. Cubuk
Barret Zoph
Dandelion Mané
Vijay Vasudevan
Quoc V. Le
135
1,775
0
24 May 2018
Neural Discrete Representation Learning
Neural Discrete Representation Learning
Aaron van den Oord
Oriol Vinyals
Koray Kavukcuoglu
BDLSSLOCL
230
5,071
0
02 Nov 2017
End-to-End Learning of Semantic Grasping
End-to-End Learning of Semantic Grasping
Eric Jang
Sudheendra Vijayanarasimhan
P. Pastor
Julian Ibarz
Sergey Levine
69
86
0
06 Jul 2017
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,426
0
10 Dec 2015
Deep Learning Face Attributes in the Wild
Deep Learning Face Attributes in the Wild
Ziwei Liu
Ping Luo
Xiaogang Wang
Xiaoou Tang
CVBM
247
8,426
0
28 Nov 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
429
43,814
0
01 May 2014
1