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QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity
v1v2 (latest)

QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity

20 December 2022
Siyu Huang
Jie An
D. Wei
Jiebo Luo
Hanspeter Pfister
    DiffM
ArXiv (abs)PDFHTML

Papers citing "QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity"

6 / 56 papers shown
Title
A Learned Representation For Artistic Style
A Learned Representation For Artistic Style
Vincent Dumoulin
Jonathon Shlens
M. Kudlur
GAN
303
1,166
0
24 Oct 2016
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Perceptual Losses for Real-Time Style Transfer and Super-Resolution
Justin Johnson
Alexandre Alahi
Li Fei-Fei
SupR
237
10,249
0
27 Mar 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,115
0
22 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.6K
100,386
0
04 Sep 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
413
43,667
0
01 May 2014
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