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TGHop: An Explainable, Efficient and Lightweight Method for Texture
  Generation

TGHop: An Explainable, Efficient and Lightweight Method for Texture Generation

8 July 2021
Xuejing Lei
Ganning Zhao
Kaitai Zhang
C.-C. Jay Kuo
ArXivPDFHTML

Papers citing "TGHop: An Explainable, Efficient and Lightweight Method for Texture Generation"

25 / 25 papers shown
Title
AnomalyHop: An SSL-based Image Anomaly Localization Method
AnomalyHop: An SSL-based Image Anomaly Localization Method
Kaitai Zhang
Bin Wang
Wen Wang
Fahad Sohrab
Moncef Gabbouj
C.-C. Jay Kuo
57
16
0
08 May 2021
R-PointHop: A Green, Accurate, and Unsupervised Point Cloud Registration
  Method
R-PointHop: A Green, Accurate, and Unsupervised Point Cloud Registration Method
Pranav Kadam
Min Zhang
Shan Liu
C.-C. Jay Kuo
3DPC
37
58
0
15 Mar 2021
DefakeHop: A Light-Weight High-Performance Deepfake Detector
DefakeHop: A Light-Weight High-Performance Deepfake Detector
Hong-Shuo Chen
Mozhdeh Rouhsedaghat
Hamza Ghani
Shuowen Hu
Suya You
C.-C. Jay Kuo
44
78
0
11 Mar 2021
Successive Subspace Learning: An Overview
Successive Subspace Learning: An Overview
Mozhdeh Rouhsedaghat
Masoud Monajatipoor
Zohreh Azizi
C.-C. Jay Kuo
32
15
0
27 Feb 2021
VoxelHop: Successive Subspace Learning for ALS Disease Classification
  Using Structural MRI
VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI
Xiaofeng Liu
Fangxu Xing
Chao Yang
C.-C. Jay Kuo
S. Babu
Xiaofeng Liu
Thomas Jenkins
Jonghye Woo
32
30
0
13 Jan 2021
NITES: A Non-Parametric Interpretable Texture Synthesis Method
NITES: A Non-Parametric Interpretable Texture Synthesis Method
Xuejing Lei
Ganning Zhao
C.-C. Jay Kuo
36
19
0
02 Sep 2020
Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
Pranav Kadam
Min Zhang
Shan Liu
C.-C. Jay Kuo
3DPC
28
23
0
02 Sep 2020
Unsupervised Feedforward Feature (UFF) Learning for Point Cloud
  Classification and Segmentation
Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation
Min Zhang
Pranav Kadam
Shan Liu
C.-C. Jay Kuo
3DPC
40
20
0
02 Sep 2020
FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method
FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method
Mozhdeh Rouhsedaghat
Yifan Wang
Xiou Ge
Shuowen Hu
Suya You
C.-C. Jay Kuo
CVBM
46
42
0
18 Jul 2020
PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model
  for Image Classification
PixelHop++: A Small Successive-Subspace-Learning-Based (SSL-based) Model for Image Classification
Yueru Chen
Mozhdeh Rouhsedaghat
Suya You
Raghuveer Rao
C.-C. Jay Kuo
46
70
0
08 Feb 2020
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal
  and Image Processing
Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
V. Monga
Yuelong Li
Yonina C. Eldar
100
1,022
0
22 Dec 2019
PointHop: An Explainable Machine Learning Method for Point Cloud
  Classification
PointHop: An Explainable Machine Learning Method for Point Cloud Classification
Min Zhang
Haoxuan You
Pranav Kadam
Shan Liu
C.-C. Jay Kuo
3DPC
32
109
0
30 Jul 2019
An Interpretable Compression and Classification System: Theory and
  Applications
An Interpretable Compression and Classification System: Theory and Applications
T. Tseng
Kai-Jiun Yang
C.-C. Jay Kuo
Shang-Ho
S. Tsai
44
11
0
21 Jul 2019
Texture Fields: Learning Texture Representations in Function Space
Texture Fields: Learning Texture Representations in Function Space
Michael Oechsle
L. Mescheder
Michael Niemeyer
Thilo Strauss
Andreas Geiger
3DH
3DV
91
299
0
17 May 2019
Re-Identification Supervised Texture Generation
Re-Identification Supervised Texture Generation
Jian Wang
Mingliang Xu
Yachun Li
Chi Zhang
Yichen Wei
3DH
83
29
0
06 Apr 2019
Visualization, Discriminability and Applications of Interpretable Saak
  Features
Visualization, Discriminability and Applications of Interpretable Saak Features
Abinaya Manimaran
T. Ramanathan
Suya You
C.-C. Jay Kuo
FAtt
67
8
0
25 Feb 2019
Interpretable Convolutional Neural Networks via Feedforward Design
Interpretable Convolutional Neural Networks via Feedforward Design
C.-C. Jay Kuo
Min Zhang
Siyang Li
Jiali Duan
Yueru Chen
59
157
0
05 Oct 2018
Visual Analytics for Explainable Deep Learning
Visual Analytics for Explainable Deep Learning
Jaegul Choo
Shixia Liu
HAI
XAI
58
236
0
07 Apr 2018
Universal Style Transfer via Feature Transforms
Universal Style Transfer via Feature Transforms
Yijun Li
Chen Fang
Jimei Yang
Zhaowen Wang
Xin Lu
Ming-Hsuan Yang
DiffM
103
990
0
23 May 2017
Diversified Texture Synthesis with Feed-forward Networks
Diversified Texture Synthesis with Feed-forward Networks
Yijun Li
Chen Fang
Jimei Yang
Zhaowen Wang
Xin Lu
Ming-Hsuan Yang
49
268
0
05 Mar 2017
Stable and Controllable Neural Texture Synthesis and Style Transfer
  Using Histogram Losses
Stable and Controllable Neural Texture Synthesis and Style Transfer Using Histogram Losses
E. Risser
Pierre Wilmot
Connelly Barnes
96
248
0
31 Jan 2017
Understanding Convolutional Neural Networks with A Mathematical Model
Understanding Convolutional Neural Networks with A Mathematical Model
C.-C. Jay Kuo
FAtt
46
374
0
14 Sep 2016
Improved Techniques for Training GANs
Improved Techniques for Training GANs
Tim Salimans
Ian Goodfellow
Wojciech Zaremba
Vicki Cheung
Alec Radford
Xi Chen
GAN
480
9,052
0
10 Jun 2016
Texture Synthesis Through Convolutional Neural Networks and Spectrum
  Constraints
Texture Synthesis Through Convolutional Neural Networks and Spectrum Constraints
Gang Liu
Y. Gousseau
Gui-Song Xia
3DV
33
56
0
04 May 2016
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
Texture Networks: Feed-forward Synthesis of Textures and Stylized Images
Dmitry Ulyanov
V. Lebedev
Andrea Vedaldi
Victor Lempitsky
3DH
56
947
0
10 Mar 2016
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