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Zhiwei Zhong - IEEE Xplore Author Profile

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Author details

Zhiwei Zhong

Publications

14

Citations

227

Publications by Year

20192024

Co-Authors:

Abdullah AbuolaimKazutoshi AkitaVikas Kumar AnandAditya AroraXiaoying Bai

Show All Co-Authors (137)

Zhiwei Zhong

Affiliation

Escuela Superior Politécnica del Litoral

ESPOL

Guayaquil, Ecuador

Computer Vision Center

Campus UAB

Barcelona, Spain

Publication Topics

Convolutional Layers,
Super-resolution Results,
Face Images,
Face Recognition,
High-resolution Images,
Image Pairs,
Image Super-resolution Challenge,
Infrared Imaging,
Intermediate Results,
L1 Loss,
Learning Rate,
Low-resolution Images

Biography

Zhiwei Zhong received the B.S. degree in computer science from Heilongjiang University, Harbin, China, in 2017. He is currently pursing the Ph.D. degree in computer science from the Harbin Institute of Technology, Harbin. His research interests include image processing, computer vision, and deep learning.(Based on document published on 3 April 2023).

Publications

14

Citations

227

Publications by Year

20192024

Co-Authors:

Abdullah Abuolaim
Kazutoshi Akita
Vikas Kumar Anand
Aditya Arora
Xiaoying Bai

Show All Co-Authors (137)

Author's Published Works

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Showing 1-14 of 14 results

Conferences (10)

Journals (4)

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Single Year
Zhiwei Zhong(14)
Junjun Jiang(12)
Xianming Liu(11)
Chenyang Wang(8)
Debin Zhao(3)
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China(6)
Escuela Superior Politécnica del Litoral, ESPOL, Guayaquil, Ecuador(3)
ETH Zurich(3)
Computer Vision Center, Campus UAB, Barcelona, Spain(2)
Department of Automation, Tsinghua University, Beijing, China(1)
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)(1)
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(1)
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
IEEE(14)
New Orleans, LA, USA(2)
Vancouver, BC, Canada(2)
Barcelona, Spain(1)
Long Beach, CA, USA(1)
Nashville, TN, USA(1)
Convolutional Layers(9)
Peak Signal-to-noise Ratio(6)
L1 Loss(5)
Convolutional Neural Network(4)
Face Images(4)

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Results

Thermal Image Super-Resolution Challenge Results - PBVS 2024

Rafael E. Rivadeneira;Angel D. Sappa;Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Peilin Chen;Shiqi Wang

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2024 | Conference Paper |

Cited by: Papers (2)

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This paper outlines the advancements and results of the Fifth Thermal Image Super-Resolution challenge, hosted at the Perception Beyond the Visible Spectrum CVPR 2024 workshop. The challenge employed a novel benchmark cross-spectral dataset consisting of 1000 thermal images, each paired with its corresponding registered RGB image. The challenge featured two tracks: Track-1 focused on Single Therma...Show More

Thermal Image Super-Resolution Challenge Results - PBVS 2024

Rafael E. Rivadeneira;Angel D. Sappa;Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Peilin Chen;Shiqi Wang

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2024 | Conference Paper |

Deep Attentional Guided Image Filtering

Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Xiangyang Ji

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 9 | Journal Article |

Cited by: Papers (12)

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Guided filter is a fundamental tool in computer vision and computer graphics, which aims to transfer structure information from the guide image to the target image. Most existing methods construct filter kernels from the guidance itself without considering the mutual dependency between the guidance and the target. However, since there typically exist significantly different edges in two images, si...Show More

Deep Attentional Guided Image Filtering

Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Xiangyang Ji

IEEE Transactions on Neural Networks and Learning Systems

Year: 2024 | Volume: 35, Issue: 9 | Journal Article |

Spatial-Frequency Mutual Learning for Face Super-Resolution

Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Xianming Liu

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2023 | Conference Paper |

Cited by: Papers (39)

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Face super-resolution (FSR) aims to reconstruct high-resolution (HR) face images from the low-resolution (LR) ones. With the advent of deep learning, the FSR technique has achieved significant breakthroughs. However, existing FSR methods either have a fixed receptive field or fail to maintain facial structure, limiting the FSRperformance. To circumvent this problem, Fourier transform is introduced...Show More

Spatial-Frequency Mutual Learning for Face Super-Resolution

Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Xianming Liu

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2023 | Conference Paper |

Thermal Image Super-Resolution Challenge Results - PBVS 2023

Rafael E. Rivadeneira;Angel D. Sappa;Boris X. Vintimilla;Chenyang Wang;Junjun Jiang;Xianming Liu;Zhiwei Zhong;Dai Bin;Li Ruodi;Li Shengye

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2023 | Conference Paper |

Cited by: Papers (8)

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This paper presents the results of two tracks from the fourth Thermal Image Super-Resolution (TISR) challenge, held at the Perception Beyond the Visible Spectrum (PBVS) 2023 workshop. Track-1 uses the same thermal image dataset as previous challenges, with 951 training images and 50 validation images at each resolution. In this track, two evaluations were conducted: the first consists of generatin...Show More

Thermal Image Super-Resolution Challenge Results - PBVS 2023

Rafael E. Rivadeneira;Angel D. Sappa;Boris X. Vintimilla;Chenyang Wang;Junjun Jiang;Xianming Liu;Zhiwei Zhong;Dai Bin;Li Ruodi;Li Shengye

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2023 | Conference Paper |

DTTR: Detecting Text with Transformers

Jing Yang;Zhiqiang You;Zhiwei Zhong;Peng Liu;Langqi Mei;Shenguang Huang

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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Recently, most transformer-based approaches have achieved considerable success on vision tasks, even better than those with convolution neural networks (CNNs). In this paper, we present a novel transformer-based model, named detecting text with transformers (DTTR), for scene text detection. In DTTR, a CNN backbone extracts local connectivity features and a transformer decoder captures global conte...Show More

DTTR: Detecting Text with Transformers

Jing Yang;Zhiqiang You;Zhiwei Zhong;Peng Liu;Langqi Mei;Shenguang Huang

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2023 | Conference Paper |

Super-Resolving Face Image by Facial Parsing Information

Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Deming Zhai;Xianming Liu

IEEE Transactions on Biometrics, Behavior, and Identity Science

Year: 2023 | Volume: 5, Issue: 4 | Journal Article |

Cited by: Papers (6)

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Face super-resolution is a technology that transforms a low-resolution face image into the corresponding high-resolution one. In this paper, we build a novel parsing map guided face super-resolution network which extracts the face prior (i.e., parsing map) directly from low-resolution face image for the following utilization. To exploit the extracted prior fully, a parsing map attention fusion blo...Show More

Super-Resolving Face Image by Facial Parsing Information

Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Deming Zhai;Xianming Liu

IEEE Transactions on Biometrics, Behavior, and Identity Science

Year: 2023 | Volume: 5, Issue: 4 | Journal Article |

Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation

Wenbo Zhao;Xianming Liu;Zhiwei Zhong;Junjun Jiang;Wei Gao;Ge Li;Xiangyang Ji

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2022 | Conference Paper |

Cited by: Papers (30)

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Point clouds upsampling is a challenging issue to gener-ate dense and uniform point clouds from the given sparse input. Most existing methods either take the end-to-end su-pervised learning based manner, where large amounts of pairs of sparse input and dense ground-truth are exploited as supervision information; or treat up-scaling of different scale factors as independent tasks, and have to build...Show More

Self-Supervised Arbitrary-Scale Point Clouds Upsampling via Implicit Neural Representation

Wenbo Zhao;Xianming Liu;Zhiwei Zhong;Junjun Jiang;Wei Gao;Ge Li;Xiangyang Ji

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2022 | Conference Paper |

Thermal Image Super-Resolution Challenge Results - PBVS 2022

Rafael E. Rivadeneira;Angel D. Sappa;Boris X. Vintimilla;Jin Kim;Dogun Kim;Zhihao Li;Yingchun Jian;Bo Yan;Leilei Cao;Fengliang Qi;Hongbin Wang;Rongyuan Wu;Lingchen Sun;Yongqiang Zhao;Lin Li;Kai Wang;Yicheng Wang;Xuanming Zhang;Huiyuan Wei;Chonghua Lv;Qigong Sun;Xiaolin Tian;Zhuang Jia;Jiakui Hu;Chenyang Wang;Zhiwei Zhong;Xianming Liu;Junjun Jiang

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2022 | Conference Paper |

Cited by: Papers (8)

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This paper presents results from the third Thermal Image Super-Resolution (TISR) challenge organized in the Perception Beyond the Visible Spectrum (PBVS) 2022 workshop. The challenge uses the same thermal image dataset as the first two challenges, with 951 training images and 50 validation images at each resolution. A set of 20 images was kept aside for testing. The evaluation tasks were to measur...Show More

Thermal Image Super-Resolution Challenge Results - PBVS 2022

Rafael E. Rivadeneira;Angel D. Sappa;Boris X. Vintimilla;Jin Kim;Dogun Kim;Zhihao Li;Yingchun Jian;Bo Yan;Leilei Cao;Fengliang Qi;Hongbin Wang;Rongyuan Wu;Lingchen Sun;Yongqiang Zhao;Lin Li;Kai Wang;Yicheng Wang;Xuanming Zhang;Huiyuan Wei;Chonghua Lv;Qigong Sun;Xiaolin Tian;Zhuang Jia;Jiakui Hu;Chenyang Wang;Zhiwei Zhong;Xianming Liu;Junjun Jiang

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2022 | Conference Paper |

Propagating Facial Prior Knowledge for Multitask Learning in Face Super-Resolution

Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Xianming Liu

IEEE Transactions on Circuits and Systems for Video Technology

Year: 2022 | Volume: 32, Issue: 11 | Journal Article |

Cited by: Papers (33)

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Existing face hallucination methods always achieve improved performance through regularizing the model with facial prior. Most of them always estimate facial prior information first and then leverage it to help the prediction of the target high-resolution face image. However, the accuracy of prior estimation is difficult to guarantee, especially for the low-resolution face image. Once the estimate...Show More

Propagating Facial Prior Knowledge for Multitask Learning in Face Super-Resolution

Chenyang Wang;Junjun Jiang;Zhiwei Zhong;Xianming Liu

IEEE Transactions on Circuits and Systems for Video Technology

Year: 2022 | Volume: 32, Issue: 11 | Journal Article |

High-Resolution Depth Maps Imaging via Attention-Based Hierarchical Multi-Modal Fusion

Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Zhiwen Chen;Xiangyang Ji

IEEE Transactions on Image Processing

Year: 2022 | Volume: 31 | Journal Article |

Cited by: Papers (30)

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Depth map records distance between the viewpoint and objects in the scene, which plays a critical role in many real-world applications. However, depth map captured by consumer-grade RGB-D cameras suffers from low spatial resolution. Guided depth map super-resolution (DSR) is a popular approach to address this problem, which attempts to restore a high-resolution (HR) depth map from the input low-re...Show More

High-Resolution Depth Maps Imaging via Attention-Based Hierarchical Multi-Modal Fusion

Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Zhiwen Chen;Xiangyang Ji

IEEE Transactions on Image Processing

Year: 2022 | Volume: 31 | Journal Article |

NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results

Abdullah Abuolaim;Radu Timofte;Michael S. Brown;Dafeng Zhang;Xiaobing Wang;Syed Waqas Zamir;Aditya Arora;Salman Khan;Munawar Hayat;Fahad Shahbaz Khan;Ling Shao;Shuai Liu;Lei Lei;Chaoyu Feng;Zhiwei Xiong;Zeyu Xiao;Ruikang Xu;Yunan Zhu;Dong Liu;Tu Vo;Si Miao;Nisarg A. Shah;Pengwei Liang;Zhiwei Zhong;Xingyu Hu;Yiqun Chen;Chenghua Li;Xiaoying Bai;Chi Zhang;Yiheng Yao;Ruipeng Gang;Sabari Nathan;Thangavelu Ragavendran;Venkatakrishnan Srinija;Venkatakrishnan Srivatsav

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2021 | Conference Paper |

Cited by: Papers (12)

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This paper provides a review of the NTIRE 2021 challenge targeting defocus deblurring using dual-pixel (DP) data. The goal of this single-track challenge was to reduce spatially varying defocus blur present in images captured with a shallow depth of field. The images used in this challenge were obtained using a DP sensor that provided a pair of DP views per captured image. Submitted solutions were...Show More

NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results

Abdullah Abuolaim;Radu Timofte;Michael S. Brown;Dafeng Zhang;Xiaobing Wang;Syed Waqas Zamir;Aditya Arora;Salman Khan;Munawar Hayat;Fahad Shahbaz Khan;Ling Shao;Shuai Liu;Lei Lei;Chaoyu Feng;Zhiwei Xiong;Zeyu Xiao;Ruikang Xu;Yunan Zhu;Dong Liu;Tu Vo;Si Miao;Nisarg A. Shah;Pengwei Liang;Zhiwei Zhong;Xingyu Hu;Yiqun Chen;Chenghua Li;Xiaoying Bai;Chi Zhang;Yiheng Yao;Ruipeng Gang;Sabari Nathan;Thangavelu Ragavendran;Venkatakrishnan Srinija;Venkatakrishnan Srivatsav

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2021 | Conference Paper |

Parsing Map Guided Multi-Scale Attention Network For Face Hallucination

Chenyang Wang;Zhiwei Zhong;Junjun Jiang;Deming Zhai;Xianming Liu

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2020 | Conference Paper |

Cited by: Papers (10)

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Face hallucination that aims to transform a low-resolution (LR) face image to a high-resolution (HR) one is an active domain-specific image super-resolution problem. The performance of existing methods is usually not satisfactory, especially when the upscaling factor is large, such as 8×. In this paper, we propose an effective two- step face hallucination method based on a deep neural network with...Show More

Parsing Map Guided Multi-Scale Attention Network For Face Hallucination

Chenyang Wang;Zhiwei Zhong;Junjun Jiang;Deming Zhai;Xianming Liu

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Year: 2020 | Conference Paper |

NTIRE 2019 Challenge on Image Enhancement: Methods and Results

Andrey Ignatov;Radu Timofte;Xiaochao Qu;Xingguang Zhou;Ting Liu;Pengfei Wan;Syed Waqas Zamir;Aditya Arora;Salman Khan;Fahad Shahbaz Khan;Ling Shao;Dongwon Park;Se Young Chun;Pablo Navarrete Michelini;Hanwen Liu;Dan Zhu;Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Muhammad Haris;Kazutoshi Akita;Tomoki Yoshida;Greg Shakhnarovich;Norimichi Ukita;Jie Liu;Cheolkon Jung;Raimondo Schettini;Simone Bianco;Claudio Cusano;Flavio Piccoli;Pengju Liu;Kai Zhang;Jingdong Liu;Jiye Liu;Hongzhi Zhang;Wangmeng Zuo;Nelson Chong Ngee Bow;Lai-Kuan Wong;John See;Jinghui Qin;Lishan Huang;Yukai Shi;Pengxu Wei;Wushao Wen;Liang Lin;Zheng Hui;Xiumei Wang;Xinbo Gao;Kanti Kumari;Vikas Kumar Anand;Mahendra Khened;Ganapathy Krishnamurthi

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2019 | Conference Paper |

Cited by: Papers (29)

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This paper reviews the first NTIRE challenge on perceptual image enhancement with the focus on proposed solutions and results. The participating teams were solving a real-world photo enhancement problem, where the goal was to map low-quality photos from the iPhone 3GS device to the same photos captured with Canon 70D DSLR camera. The considered problem embraced a number of computer vision subtasks...Show More

NTIRE 2019 Challenge on Image Enhancement: Methods and Results

Andrey Ignatov;Radu Timofte;Xiaochao Qu;Xingguang Zhou;Ting Liu;Pengfei Wan;Syed Waqas Zamir;Aditya Arora;Salman Khan;Fahad Shahbaz Khan;Ling Shao;Dongwon Park;Se Young Chun;Pablo Navarrete Michelini;Hanwen Liu;Dan Zhu;Zhiwei Zhong;Xianming Liu;Junjun Jiang;Debin Zhao;Muhammad Haris;Kazutoshi Akita;Tomoki Yoshida;Greg Shakhnarovich;Norimichi Ukita;Jie Liu;Cheolkon Jung;Raimondo Schettini;Simone Bianco;Claudio Cusano;Flavio Piccoli;Pengju Liu;Kai Zhang;Jingdong Liu;Jiye Liu;Hongzhi Zhang;Wangmeng Zuo;Nelson Chong Ngee Bow;Lai-Kuan Wong;John See;Jinghui Qin;Lishan Huang;Yukai Shi;Pengxu Wei;Wushao Wen;Liang Lin;Zheng Hui;Xiumei Wang;Xinbo Gao;Kanti Kumari;Vikas Kumar Anand;Mahendra Khened;Ganapathy Krishnamurthi

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2019 | Conference Paper |

AIM 2019 Challenge on Video Extreme Super-Resolution: Methods and Results

Dario Fuoli;Shuhang Gu;Radu Timofte;Xin Tao;Wenbo Li;Taian Guo;Zijun Deng;Liying Lu;Tao Dai;Xiaoyong Shen;Shutao Xia;Yurong Dai;Jiaya Jia;Peng Yi;Zhongyuan Wang;Kui Jiang;Junjun Jiang;Jiayi Ma;Zhiwei Zhong;Chenyang Wang;JunJun Jiang;Xianming Liu

2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)

Year: 2019 | Conference Paper |

Cited by: Papers (7)

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This paper reviews the extreme video super-resolution challenge from the AIM 2019 workshop, with emphasis on submitted solutions and results. Video extreme super-resolution x16 is a highly challenging problem, because 256 pixels need to be estimated for each single pixel in the low-resolution (LR) input. Contrary to single image super-resolution (SISR), video provides temporal information, which c...Show More

AIM 2019 Challenge on Video Extreme Super-Resolution: Methods and Results

Dario Fuoli;Shuhang Gu;Radu Timofte;Xin Tao;Wenbo Li;Taian Guo;Zijun Deng;Liying Lu;Tao Dai;Xiaoyong Shen;Shutao Xia;Yurong Dai;Jiaya Jia;Peng Yi;Zhongyuan Wang;Kui Jiang;Junjun Jiang;Jiayi Ma;Zhiwei Zhong;Chenyang Wang;JunJun Jiang;Xianming Liu

2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)

Year: 2019 | Conference Paper |

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