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Unsupervised Learning of Visual Representations by Solving Jigsaw
  Puzzles
v1v2v3 (latest)

Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

30 March 2016
M. Noroozi
Paolo Favaro
    SSL
ArXiv (abs)PDFHTML

Papers citing "Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles"

41 / 1,791 papers shown
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation
Mix-and-Match Tuning for Self-Supervised Semantic Segmentation
Xiaohang Zhan
Ziwei Liu
Ping Luo
Xiaoou Tang
Chen Change Loy
SSL
152
38
0
02 Dec 2017
Exploiting the potential of unlabeled endoscopic video data with
  self-supervised learning
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning
T. Ross
David Zimmerer
A. Vemuri
Hyunjin Park
Manuel Wiesenfarth
...
H. Kenngott
Stefanie Speidel
Annette Kopp-Schneider
Klaus Maier-Hein
Lena Maier-Hein
MedImSSL
166
134
0
27 Nov 2017
Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic
  Imagery
Cross-Domain Self-supervised Multi-task Feature Learning using Synthetic Imagery
Zhongzheng Ren
Yong Jae Lee
SSLOOD
225
216
0
24 Nov 2017
Improvements to context based self-supervised learning
Improvements to context based self-supervised learning
T. N. Mundhenk
Mark A. Lemley
Barry Y. Chen
SSL
261
124
0
17 Nov 2017
Interpreting Deep Visual Representations via Network Dissection
Interpreting Deep Visual Representations via Network Dissection
Bolei Zhou
David Bau
A. Oliva
Antonio Torralba
FAttMILM
250
353
0
15 Nov 2017
Fidelity-Weighted Learning
Fidelity-Weighted Learning
Mostafa Dehghani
Arash Mehrjou
Stephan Gouws
J. Kamps
Bernhard Schölkopf
NoLaFedML
193
76
0
08 Nov 2017
Generating Music Medleys via Playing Music Puzzle Games
Generating Music Medleys via Playing Music Puzzle Games
Yu-Siang Huang
Szu-Yu Chou
Yi-Hsuan Yang
122
6
0
13 Sep 2017
Unsupervised feature learning with discriminative encoder
Unsupervised feature learning with discriminative encoder
Gaurav Pandey
Ambedkar Dukkipati
SSL
107
6
0
03 Sep 2017
ShapeCodes: Self-Supervised Feature Learning by Lifting Views to
  Viewgrids
ShapeCodes: Self-Supervised Feature Learning by Lifting Views to Viewgrids
Dinesh Jayaraman
Ruohan Gao
Kristen Grauman
SSL
290
5
0
01 Sep 2017
Multi-task Self-Supervised Visual Learning
Multi-task Self-Supervised Visual Learning
Carl Doersch
Andrew Zisserman
SSL
298
658
0
25 Aug 2017
Representation Learning by Learning to Count
Representation Learning by Learning to Count
M. Noroozi
Hamed Pirsiavash
Paolo Favaro
SSL
224
378
0
22 Aug 2017
Discovery of Visual Semantics by Unsupervised and Self-Supervised
  Representation Learning
Discovery of Visual Semantics by Unsupervised and Self-Supervised Representation Learning
Gustav Larsson
SSLVLM
142
6
0
19 Aug 2017
WebVision Database: Visual Learning and Understanding from Web Data
WebVision Database: Visual Learning and Understanding from Web Data
Wen Li
Limin Wang
Wei Li
E. Agustsson
Luc Van Gool
VLM
310
487
0
09 Aug 2017
Self-supervised Learning of Pose Embeddings from Spatiotemporal
  Relations in Videos
Self-supervised Learning of Pose Embeddings from Spatiotemporal Relations in VideosIEEE International Conference on Computer Vision (ICCV), 2017
Ömer Sümer
Tobias Dencker
Bjorn Ommer
3DHSSL
138
28
0
07 Aug 2017
Unsupervised Representation Learning by Sorting Sequences
Unsupervised Representation Learning by Sorting Sequences
Hsin-Ying Lee
Jia-Bin Huang
Maneesh Kumar Singh
Ming-Hsuan Yang
SSLDRL
344
562
0
03 Aug 2017
Automatic Curation of Golf Highlights using Multimodal Excitement
  Features
Automatic Curation of Golf Highlights using Multimodal Excitement Features
Michele Merler
D. Joshi
Q. Nguyen
Stephen Hammer
John Kent
John R. Smith
Rogerio Feris
VGen
114
19
0
22 Jul 2017
Unsupervised learning of object frames by dense equivariant image
  labelling
Unsupervised learning of object frames by dense equivariant image labellingNeural Information Processing Systems (NeurIPS), 2017
James Thewlis
Hakan Bilen
Andrea Vedaldi
OCL
224
26
0
09 Jun 2017
Look, Listen and Learn
Look, Listen and Learn
Relja Arandjelović
Andrew Zisserman
SSL
406
986
0
23 May 2017
WebVision Challenge: Visual Learning and Understanding With Web Data
WebVision Challenge: Visual Learning and Understanding With Web Data
Wen Li
Limin Wang
Wei Li
E. Agustsson
Jesse Berent
Abhinav Gupta
Rahul Sukthankar
Luc Van Gool
VLM
110
21
0
16 May 2017
Unsupervised learning of object landmarks by factorized spatial
  embeddings
Unsupervised learning of object landmarks by factorized spatial embeddings
James Thewlis
Hakan Bilen
Andrea Vedaldi
OCLSSL
260
170
0
05 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual
  Representations
Network Dissection: Quantifying Interpretability of Deep Visual Representations
David Bau
Bolei Zhou
A. Khosla
A. Oliva
Antonio Torralba
MILMFAtt
604
1,676
1
19 Apr 2017
Unsupervised Learning by Predicting Noise
Unsupervised Learning by Predicting Noise
Piotr Bojanowski
Armand Joulin
OODSSL
170
299
0
18 Apr 2017
Weakly-Supervised Spatial Context Networks
Weakly-Supervised Spatial Context Networks
Zuxuan Wu
L. Davis
Leonid Sigal
SSL3DPC
140
1
0
10 Apr 2017
DeepPermNet: Visual Permutation Learning
DeepPermNet: Visual Permutation Learning
Rodrigo Santa Cruz
Basura Fernando
A. Cherian
Stephen Gould
SSL
155
108
0
10 Apr 2017
Unsupervised Holistic Image Generation from Key Local Patches
Unsupervised Holistic Image Generation from Key Local Patches
Donghoon Lee
Sangdoo Yun
Sungjoon Choi
Hwiyeon Yoo
Ming-Hsuan Yang
Songhwai Oh
GAN
169
12
0
31 Mar 2017
Colorization as a Proxy Task for Visual Understanding
Colorization as a Proxy Task for Visual Understanding
Gustav Larsson
Michael Maire
Gregory Shakhnarovich
SSL
597
513
0
11 Mar 2017
PixelNet: Representation of the pixels, by the pixels, and for the
  pixels
PixelNet: Representation of the pixels, by the pixels, and for the pixels
Aayush Bansal
Xinlei Chen
Bryan C. Russell
Abhinav Gupta
Deva Ramanan
SSeg
202
122
0
21 Feb 2017
An Adversarial Regularisation for Semi-Supervised Training of Structured
  Output Neural Networks
An Adversarial Regularisation for Semi-Supervised Training of Structured Output Neural NetworksNeural Information Processing Systems (NeurIPS), 2017
Mateusz Koziñski
Loïc Simon
F. Jurie
GAN
146
18
0
08 Feb 2017
Loss is its own Reward: Self-Supervision for Reinforcement Learning
Loss is its own Reward: Self-Supervision for Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2016
Evan Shelhamer
Parsa Mahmoudieh
Max Argus
Trevor Darrell
SSL
187
192
0
21 Dec 2016
Learning Features by Watching Objects Move
Learning Features by Watching Objects MoveComputer Vision and Pattern Recognition (CVPR), 2016
Deepak Pathak
Ross B. Girshick
Piotr Dollár
Trevor Darrell
Bharath Hariharan
SSLVOSOCL
297
534
0
19 Dec 2016
Understanding image motion with group representations
Understanding image motion with group representations
Andrew Jaegle
Stephen Phillips
Daphne Ippolito
Kostas Daniilidis
GAN
127
1
0
01 Dec 2016
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel
  Prediction
Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
SSLDRL
370
689
0
29 Nov 2016
Quad-networks: unsupervised learning to rank for interest point
  detection
Quad-networks: unsupervised learning to rank for interest point detection
Nikolay Savinov
Akihito Seki
Lubor Ladicky
Torsten Sattler
Marc Pollefeys
3DPC
243
184
0
22 Nov 2016
Semi-Supervised Learning with Context-Conditional Generative Adversarial
  Networks
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
Emily L. Denton
Sam Gross
Rob Fergus
GAN
164
159
0
19 Nov 2016
Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All
  Networks
Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks
Eder Santana
Matthew S. Emigh
Pablo Zegers
José C. Príncipe
BDL
404
16
0
31 Oct 2016
What makes ImageNet good for transfer learning?
What makes ImageNet good for transfer learning?
Minyoung Huh
Pulkit Agrawal
Alexei A. Efros
OODSSegVLMSSL
379
701
0
30 Aug 2016
Deep Successor Reinforcement Learning
Deep Successor Reinforcement Learning
Tejas D. Kulkarni
A. Saeedi
Simanta Gautam
S. Gershman
242
220
0
08 Jun 2016
Asynchrony begets Momentum, with an Application to Deep Learning
Asynchrony begets Momentum, with an Application to Deep LearningAllerton Conference on Communication, Control, and Computing (Allerton), 2016
Jeff Donahue
Philipp Krahenbuhl
Stefan Hadjis
Christopher Ré
481
1,888
0
31 May 2016
Learning Local Descriptors by Optimizing the Keypoint-Correspondence
  Criterion: Applications to Face Matching, Learning from Unlabeled Videos and
  3D-Shape Retrieval
Learning Local Descriptors by Optimizing the Keypoint-Correspondence Criterion: Applications to Face Matching, Learning from Unlabeled Videos and 3D-Shape Retrieval
Nenad Markuš
Igor S. Pandzic
Jörgen Ahlberg
3DV
236
4
0
30 Mar 2016
Colorful Image Colorization
Colorful Image Colorization
Richard Y. Zhang
Phillip Isola
Alexei A. Efros
628
3,670
0
28 Mar 2016
Learning Representations for Automatic Colorization
Learning Representations for Automatic Colorization
Gustav Larsson
Michael Maire
Gregory Shakhnarovich
VLMSSL
433
1,046
0
22 Mar 2016
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