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Zhengtao Wang - IEEE Xplore Author Profile
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Zhengtao Wang

Publications
4
Citations
786
Publications by Year
20172017
Co-Authors:
Show All Co-Authors (79)
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Zhengtao Wang

Affiliation

School of Electronic Engineering / Center of Robotics, University of Electronic Science and Technology of China

Publication Topics

Publications
4
Citations
786
Publications by Year
20172017
Co-Authors:
Show All Co-Authors (79)
Author's Published Works

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Towards thinner convolutional neural networks through gradually global pruning

Zhengtao Wang;Ce Zhu;Zhiqiang Xia;Qi Guo;Yipeng Liu

2017 IEEE International Conference on Image Processing (ICIP)
Year: 2017 | Conference Paper |
Cited by: Papers (2)
Deep network pruning is an effective method to reduce the storage and computation cost of deep neural networks when applying them to resource-limited devices. Among many pruning granularities, neuron level pruning will remove redundant neurons and filters in the model and result in thinner networks. In this paper, we propose a gradually global pruning scheme for neuron level pruning. In each pruni...Show More

Towards thinner convolutional neural networks through gradually global pruning

Zhengtao Wang;Ce Zhu;Zhiqiang Xia;Qi Guo;Yipeng Liu

Year: 2017 | Conference Paper |

Attribute-controlled face photo synthesis from simple line drawing

Qi Guo;Ce Zhu;Zhiqiang Xia;Zhengtao Wang;Yipeng Liu

2017 IEEE International Conference on Image Processing (ICIP)
Year: 2017 | Conference Paper |
Cited by: Papers (9)
Face photo synthesis from simple line drawing is a one-to-many task as simple line drawing merely contains the contour of human face. Previous exemplar-based methods are over-dependent on the datasets and are hard to generalize to complicated natural scenes. Recently, several works utilize deep neural networks to increase the generalization, but they are still limited in the controllability of the...Show More

Attribute-controlled face photo synthesis from simple line drawing

Qi Guo;Ce Zhu;Zhiqiang Xia;Zhengtao Wang;Yipeng Liu

Year: 2017 | Conference Paper |

Image ordinal estimation: Classification and regression benefit each other

Chao Zhang;Ce Zhu;Yipeng Liu;Hongdiao Wen;Zhengtao Wang

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
Year: 2017 | Conference Paper |
Cited by: Papers (4)
General multi-task learning requires multi-domain knowledges. In this paper, we present a double-task learning model that implements simultaneously classification and regression by only one domain knowledge: ordinal value. We jointly optimize category classification and score regression by two sibling loss in double-task convolutional neural network (DTCNN), in which category and score can be conv...Show More

Image ordinal estimation: Classification and regression benefit each other

Chao Zhang;Ce Zhu;Yipeng Liu;Hongdiao Wen;Zhengtao Wang

Year: 2017 | Conference Paper |

NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang;Lei Zhang;Bee Lim;Sanghyun Son;Heewon Kim;Seungjun Nah;Kyoung Mu Lee;Xintao Wang;Yapeng Tian;Ke Yu;Yulun Zhang;Shixiang Wu;Chao Dong;Liang Lin;Yu Qiao;Chen Change Loy;Woong Bae;Jaejun Yoo;Yoseob Han;Jong Chul Ye;Jae-Seok Choi;Munchurl Kim;Yuchen Fan;Jiahui Yu;Wei Han;Ding Liu;Haichao Yu;Zhangyang Wang;Honghui Shi;Xinchao Wang;Thomas S. Huang;Yunjin Chen;Kai Zhang;Wangmeng Zuo;Zhimin Tang;Linkai Luo;Shaohui Li;Min Fu;Lei Cao;Wen Heng;Giang Bui;Truc Le;Ye Duan;Dacheng Tao;Ruxin Wang;Xu Lin;Jianxin Pang;Jinchang Xu;Yu Zhao;Xiangyu Xu;Jinshan Pan;Deqing Sun;Yujin Zhang;Xibin Song;Yuchao Dai;Xueying Qin;Xuan-Phung Huynh;Tiantong Guo;Hojjat Seyed Mousavi;Tiep Huu Vu;Vishal Monga;Cristovao Cruz;Karen Egiazarian;Vladimir Katkovnik;Rakesh Mehta;Arnav Kumar Jain;Abhinav Agarwalla;Ch V. Sai Praveen;Ruofan Zhou;Hongdiao Wen;Che Zhu;Zhiqiang Xia;Zhengtao Wang;Qi Guo

2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2017 | Conference Paper |
This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2 ...Show More

NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

Radu Timofte;Eirikur Agustsson;Luc Van Gool;Ming-Hsuan Yang;Lei Zhang;Bee Lim;Sanghyun Son;Heewon Kim;Seungjun Nah;Kyoung Mu Lee;Xintao Wang;Yapeng Tian;Ke Yu;Yulun Zhang;Shixiang Wu;Chao Dong;Liang Lin;Yu Qiao;Chen Change Loy;Woong Bae;Jaejun Yoo;Yoseob Han;Jong Chul Ye;Jae-Seok Choi;Munchurl Kim;Yuchen Fan;Jiahui Yu;Wei Han;Ding Liu;Haichao Yu;Zhangyang Wang;Honghui Shi;Xinchao Wang;Thomas S. Huang;Yunjin Chen;Kai Zhang;Wangmeng Zuo;Zhimin Tang;Linkai Luo;Shaohui Li;Min Fu;Lei Cao;Wen Heng;Giang Bui;Truc Le;Ye Duan;Dacheng Tao;Ruxin Wang;Xu Lin;Jianxin Pang;Jinchang Xu;Yu Zhao;Xiangyu Xu;Jinshan Pan;Deqing Sun;Yujin Zhang;Xibin Song;Yuchao Dai;Xueying Qin;Xuan-Phung Huynh;Tiantong Guo;Hojjat Seyed Mousavi;Tiep Huu Vu;Vishal Monga;Cristovao Cruz;Karen Egiazarian;Vladimir Katkovnik;Rakesh Mehta;Arnav Kumar Jain;Abhinav Agarwalla;Ch V. Sai Praveen;Ruofan Zhou;Hongdiao Wen;Che Zhu;Zhiqiang Xia;Zhengtao Wang;Qi Guo

Year: 2017 | Conference Paper |

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