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. 1807.00734
  4. Cited By
The relativistic discriminator: a key element missing from standard GAN

The relativistic discriminator: a key element missing from standard GAN

2 July 2018
Alexia Jolicoeur-Martineau
    GAN
ArXivPDFHTML

Papers citing "The relativistic discriminator: a key element missing from standard GAN"

24 / 24 papers shown
Title
Fast Text-to-Audio Generation with Adversarial Post-Training
Fast Text-to-Audio Generation with Adversarial Post-Training
Zachary Novack
Zach Evans
Zack Zukowski
Josiah Taylor
CJ Carr
...
Adnan Al-Sinan
Gian Marco Iodice
Julian McAuley
Taylor Berg-Kirkpatrick
Jordi Pons
55
0
0
13 May 2025
MFSR-GAN: Multi-Frame Super-Resolution with Handheld Motion Modeling
MFSR-GAN: Multi-Frame Super-Resolution with Handheld Motion Modeling
Fadeel Sher Khan
Joshua Ebenezer
Hamid Sheikh
Seok-Jun Lee
100
0
0
28 Feb 2025
Face Mask Removal with Region-attentive Face Inpainting
Face Mask Removal with Region-attentive Face Inpainting
Minmin Yang
CVBM
82
0
0
10 Sep 2024
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can
  Scale Up
TransGAN: Two Pure Transformers Can Make One Strong GAN, and That Can Scale Up
Yi Ding
Shiyu Chang
Zhangyang Wang
ViT
69
389
0
14 Feb 2021
Look here! A parametric learning based approach to redirect visual
  attention
Look here! A parametric learning based approach to redirect visual attention
Youssef A. Mejjati
Celso F. Gomez
K. Kim
Eli Shechtman
Zoya Bylinskii
DiffM
3DH
33
15
0
12 Aug 2020
GANs beyond divergence minimization
GANs beyond divergence minimization
Alexia Jolicoeur-Martineau
GAN
31
11
0
06 Sep 2018
Spectral Normalization for Generative Adversarial Networks
Spectral Normalization for Generative Adversarial Networks
Takeru Miyato
Toshiki Kataoka
Masanori Koyama
Yuichi Yoshida
ODL
137
4,421
0
16 Feb 2018
Pros and Cons of GAN Evaluation Measures
Pros and Cons of GAN Evaluation Measures
Ali Borji
ELM
EGVM
57
874
0
09 Feb 2018
PacGAN: The power of two samples in generative adversarial networks
PacGAN: The power of two samples in generative adversarial networks
Zinan Lin
A. Khetan
Giulia Fanti
Sewoong Oh
GAN
52
333
0
12 Dec 2017
Are GANs Created Equal? A Large-Scale Study
Are GANs Created Equal? A Large-Scale Study
Mario Lucic
Karol Kurach
Marcin Michalski
Sylvain Gelly
Olivier Bousquet
EGVM
46
1,008
0
28 Nov 2017
How Generative Adversarial Networks and Their Variants Work: An Overview
How Generative Adversarial Networks and Their Variants Work: An Overview
Yongjun Hong
Uiwon Hwang
Jaeyoon Yoo
Sungroh Yoon
GAN
60
155
0
16 Nov 2017
Sobolev GAN
Sobolev GAN
Youssef Mroueh
Chun-Liang Li
Tom Sercu
Anant Raj
Yu Cheng
29
117
0
14 Nov 2017
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At
  Every Step
Many Paths to Equilibrium: GANs Do Not Need to Decrease a Divergence At Every Step
W. Fedus
Mihaela Rosca
Balaji Lakshminarayanan
Andrew M. Dai
S. Mohamed
Ian Goodfellow
GAN
49
210
0
23 Oct 2017
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash
  Equilibrium
GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
M. Heusel
Hubert Ramsauer
Thomas Unterthiner
Bernhard Nessler
Sepp Hochreiter
67
464
0
26 Jun 2017
Fisher GAN
Fisher GAN
Youssef Mroueh
Tom Sercu
GAN
AI4CE
41
132
0
26 May 2017
On Convergence and Stability of GANs
On Convergence and Stability of GANs
Naveen Kodali
Jacob D. Abernethy
James Hays
Z. Kira
GAN
46
87
0
19 May 2017
Improved Training of Wasserstein GANs
Improved Training of Wasserstein GANs
Ishaan Gulrajani
Faruk Ahmed
Martín Arjovsky
Vincent Dumoulin
Aaron Courville
GAN
137
9,509
0
31 Mar 2017
Towards Principled Methods for Training Generative Adversarial Networks
Towards Principled Methods for Training Generative Adversarial Networks
Martín Arjovsky
M. Nault
GAN
74
2,102
0
17 Jan 2017
Least Squares Generative Adversarial Networks
Least Squares Generative Adversarial Networks
Xudong Mao
Qing Li
Haoran Xie
Raymond Y. K. Lau
Zhen Wang
Stephen Paul Smolley
GAN
255
4,554
0
13 Nov 2016
Improved Techniques for Training GANs
Improved Techniques for Training GANs
Tim Salimans
Ian Goodfellow
Wojciech Zaremba
Vicki Cheung
Alec Radford
Xi Chen
GAN
371
8,999
0
10 Jun 2016
f-GAN: Training Generative Neural Samplers using Variational Divergence
  Minimization
f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization
Sebastian Nowozin
Botond Cseke
Ryota Tomioka
GAN
93
1,648
0
02 Jun 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
232
13,968
0
19 Nov 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
328
43,154
0
11 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
844
149,474
0
22 Dec 2014
1