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GAN Dissection: Visualizing and Understanding Generative Adversarial
  Networks

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks

26 November 2018
David Bau
Jun-Yan Zhu
Hendrik Strobelt
Bolei Zhou
J. Tenenbaum
William T. Freeman
Antonio Torralba
    GAN
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Papers citing "GAN Dissection: Visualizing and Understanding Generative Adversarial Networks"

31 / 31 papers shown
Title
Decision-Making with Auto-Encoding Variational Bayes
Decision-Making with Auto-Encoding Variational Bayes
Romain Lopez
Pierre Boyeau
Nir Yosef
Michael I. Jordan
Jeffrey Regier
BDL
365
10,591
0
17 Feb 2020
Video-to-Video Synthesis
Video-to-Video Synthesis
Ting-Chun Wang
Ming-Yuan Liu
Jun-Yan Zhu
Guilin Liu
Andrew Tao
Jan Kautz
Bryan Catanzaro
GAN
VGen
93
988
0
20 Aug 2018
Unified Perceptual Parsing for Scene Understanding
Unified Perceptual Parsing for Scene Understanding
Tete Xiao
Yingcheng Liu
Bolei Zhou
Yuning Jiang
Jian Sun
OCL
VOS
179
1,883
0
26 Jul 2018
Self-Attention Generative Adversarial Networks
Self-Attention Generative Adversarial Networks
Han Zhang
Ian Goodfellow
Dimitris N. Metaxas
Augustus Odena
GAN
131
3,725
0
21 May 2018
On the importance of single directions for generalization
On the importance of single directions for generalization
Ari S. Morcos
David Barrett
Neil C. Rabinowitz
M. Botvinick
64
333
0
19 Mar 2018
Spectral Normalization for Generative Adversarial Networks
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato
Toshiki Kataoka
Masanori Koyama
Yuichi Yoshida
ODL
155
4,437
0
16 Feb 2018
Pros and Cons of GAN Evaluation Measures
Pros and Cons of GAN Evaluation Measures
Ali Borji
ELM
EGVM
65
874
0
09 Feb 2018
Interpreting Deep Visual Representations via Network Dissection
Interpreting Deep Visual Representations via Network Dissection
Bolei Zhou
David Bau
A. Oliva
Antonio Torralba
FAtt
MILM
58
324
0
15 Nov 2017
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
139
3,001
0
08 Nov 2017
Progressive Growing of GANs for Improved Quality, Stability, and
  Variation
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Tero Karras
Timo Aila
S. Laine
J. Lehtinen
GAN
119
7,351
0
27 Oct 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
MILM
FAtt
144
1,514
1
19 Apr 2017
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection
A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection
Xinyu Wang
Abhinav Shrivastava
Abhinav Gupta
ObjD
80
572
0
11 Apr 2017
Improved Training of Wasserstein GANs
Improved Training of Wasserstein GANs
Ishaan Gulrajani
Faruk Ahmed
Martín Arjovsky
Vincent Dumoulin
Aaron Courville
GAN
191
9,545
0
31 Mar 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
175
5,986
0
04 Mar 2017
Image-to-Image Translation with Conditional Adversarial Networks
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola
Jun-Yan Zhu
Tinghui Zhou
Alexei A. Efros
SSeg
311
19,640
0
21 Nov 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based
  Localization
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
270
19,981
0
07 Oct 2016
Generative Visual Manipulation on the Natural Image Manifold
Generative Visual Manipulation on the Natural Image Manifold
Jun-Yan Zhu
Philipp Krahenbuhl
Eli Shechtman
Alexei A. Efros
GAN
69
1,396
0
12 Sep 2016
Adversarially Learned Inference
Adversarially Learned Inference
Vincent Dumoulin
Ishmael Belghazi
Ben Poole
Olivier Mastropietro
Alex Lamb
Martín Arjovsky
Aaron Courville
GAN
72
1,314
0
02 Jun 2016
Asynchrony begets Momentum, with an Application to Deep Learning
Asynchrony begets Momentum, with an Application to Deep Learning
Jeff Donahue
Philipp Krahenbuhl
Stefan Hadjis
Christopher Ré
92
141
0
31 May 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Faster Eigenvector Computation via Shift-and-Invert Preconditioning
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
258
78
0
26 May 2016
Learning Dense Correspondence via 3D-guided Cycle Consistency
Learning Dense Correspondence via 3D-guided Cycle Consistency
Tinghui Zhou
Philipp Krahenbuhl
Mathieu Aubry
Qi-Xing Huang
Alexei A. Efros
130
98
0
18 Apr 2016
Generating Images with Perceptual Similarity Metrics based on Deep
  Networks
Generating Images with Perceptual Similarity Metrics based on Deep Networks
Alexey Dosovitskiy
Thomas Brox
DRL
GAN
89
1,140
0
08 Feb 2016
Unsupervised Representation Learning with Deep Convolutional Generative
  Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Alec Radford
Luke Metz
Soumith Chintala
GAN
OOD
243
14,005
0
19 Nov 2015
Deep multi-scale video prediction beyond mean square error
Deep multi-scale video prediction beyond mean square error
Michaël Mathieu
Camille Couprie
Yann LeCun
GAN
122
1,882
0
17 Nov 2015
Deep Generative Image Models using a Laplacian Pyramid of Adversarial
  Networks
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
Emily L. Denton
Soumith Chintala
Arthur Szlam
Rob Fergus
GAN
90
2,241
0
18 Jun 2015
LSUN: Construction of a Large-scale Image Dataset using Deep Learning
  with Humans in the Loop
LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop
Feng Yu
Ari Seff
Yinda Zhang
Shuran Song
Thomas Funkhouser
Jianxiong Xiao
67
2,336
0
10 Jun 2015
Visualizing and Understanding Recurrent Networks
Visualizing and Understanding Recurrent Networks
A. Karpathy
Justin Johnson
Li Fei-Fei
HAI
111
1,101
0
05 Jun 2015
Object Detectors Emerge in Deep Scene CNNs
Object Detectors Emerge in Deep Scene CNNs
Bolei Zhou
A. Khosla
Àgata Lapedriza
A. Oliva
Antonio Torralba
ObjD
135
1,283
0
22 Dec 2014
Understanding Deep Image Representations by Inverting Them
Understanding Deep Image Representations by Inverting Them
Aravindh Mahendran
Andrea Vedaldi
FAtt
107
1,963
0
26 Nov 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
305
7,289
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
579
15,874
0
12 Nov 2013
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