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Learning What and Where to Draw

Learning What and Where to Draw

8 October 2016
Scott E. Reed
Zeynep Akata
S. Mohan
Samuel Tenka
Bernt Schiele
Honglak Lee
    DRL
    GAN
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Papers citing "Learning What and Where to Draw"

20 / 70 papers shown
Title
Unsupervised Learning of Object Landmarks through Conditional Image
  Generation
Unsupervised Learning of Object Landmarks through Conditional Image Generation
Tomas Jakab
Ankush Gupta
Hakan Bilen
Andrea Vedaldi
SSL
19
252
0
20 Jun 2018
Fast-converging Conditional Generative Adversarial Networks for Image
  Synthesis
Fast-converging Conditional Generative Adversarial Networks for Image Synthesis
Chengcheng Li
Z. Wang
Hairong Qi
GAN
11
29
0
05 May 2018
MC-GAN: Multi-conditional Generative Adversarial Network for Image
  Synthesis
MC-GAN: Multi-conditional Generative Adversarial Network for Image Synthesis
Hyojin Park
Y. Yoo
Nojun Kwak
GAN
14
58
0
03 May 2018
A Variational U-Net for Conditional Appearance and Shape Generation
A Variational U-Net for Conditional Appearance and Shape Generation
Patrick Esser
E. Sutter
Bjorn Ommer
28
417
0
12 Apr 2018
Unsupervised Discovery of Object Landmarks as Structural Representations
Unsupervised Discovery of Object Landmarks as Structural Representations
Y. Zhang
Yijie Guo
Yixin Jin
Yijun Luo
Zhiyuan He
Honglak Lee
OCL
26
194
0
12 Apr 2018
Modular Generative Adversarial Networks
Modular Generative Adversarial Networks
Bo-Lu Zhao
B. Chang
Zequn Jie
Leonid Sigal
GAN
25
80
0
10 Apr 2018
Multimodal Explanations: Justifying Decisions and Pointing to the
  Evidence
Multimodal Explanations: Justifying Decisions and Pointing to the Evidence
Dong Huk Park
Lisa Anne Hendricks
Zeynep Akata
Anna Rohrbach
Bernt Schiele
Trevor Darrell
Marcus Rohrbach
35
418
0
15 Feb 2018
Geometry-Contrastive GAN for Facial Expression Transfer
Geometry-Contrastive GAN for Facial Expression Transfer
Fengchun Qiao
Nai-Ming Yao
Zirui Jiao
Zhihao Li
Hui Chen
Hongan Wang
CVBM
GAN
14
51
0
06 Feb 2018
Structured Generative Adversarial Networks
Structured Generative Adversarial Networks
Zhijie Deng
H. M. Zhang
Xiaodan Liang
Luona Yang
Shizhen Xu
Jun Zhu
Eric P. Xing
GAN
31
53
0
02 Nov 2017
Generative Adversarial Networks: An Overview
Generative Adversarial Networks: An Overview
Antonia Creswell
Tom White
Vincent Dumoulin
Kai Arulkumaran
B. Sengupta
Anil A Bharath
GAN
25
2,967
0
19 Oct 2017
Conditional Adversarial Network for Semantic Segmentation of Brain Tumor
Conditional Adversarial Network for Semantic Segmentation of Brain Tumor
Mina Rezaei
Konstantin Harmuth
Willi Gierke
Thomas Kellermeier
Martin Fischer
Haojin Yang
Christoph Meinel
GAN
MedIm
22
120
0
17 Aug 2017
Generative Semantic Manipulation with Contrasting GAN
Generative Semantic Manipulation with Contrasting GAN
Xiaodan Liang
H. M. Zhang
Eric P. Xing
GAN
15
53
0
01 Aug 2017
Semantic Image Synthesis via Adversarial Learning
Semantic Image Synthesis via Adversarial Learning
Hao Dong
Simiao Yu
Chao Wu
Yike Guo
GAN
12
265
0
21 Jul 2017
The Pose Knows: Video Forecasting by Generating Pose Futures
The Pose Knows: Video Forecasting by Generating Pose Futures
Jacob Walker
Kenneth Marino
Abhinav Gupta
M. Hebert
22
348
0
28 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
27
11
0
31 Mar 2017
I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation
I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation
Hao Dong
Jingqing Zhang
Douglas McIlwraith
Yike Guo
25
58
0
20 Mar 2017
Attentive Explanations: Justifying Decisions and Pointing to the
  Evidence
Attentive Explanations: Justifying Decisions and Pointing to the Evidence
Dong Huk Park
Lisa Anne Hendricks
Zeynep Akata
Bernt Schiele
Trevor Darrell
Marcus Rohrbach
AAML
16
79
0
14 Dec 2016
Unrolled Generative Adversarial Networks
Unrolled Generative Adversarial Networks
Luke Metz
Ben Poole
David Pfau
Jascha Narain Sohl-Dickstein
GAN
25
1,000
0
07 Nov 2016
Learning Deep Representations of Fine-grained Visual Descriptions
Learning Deep Representations of Fine-grained Visual Descriptions
Scott E. Reed
Zeynep Akata
Bernt Schiele
Honglak Lee
OCL
VLM
163
840
0
17 May 2016
Pixel Recurrent Neural Networks
Pixel Recurrent Neural Networks
Aaron van den Oord
Nal Kalchbrenner
Koray Kavukcuoglu
SSeg
GAN
225
2,543
0
25 Jan 2016
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