Zaoxing Liu - IEEE Xplore Author Profile

Scheduled Maintenance on Monday 1/13/2025

Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Access provided by:

MIT Libraries

Access provided by:

MIT Libraries

ADVANCED SEARCH

Author details

Zaoxing Liu

Publications

4

Citations

4

Publications by Year

20232025

Co-Authors:

Ayse K. CoskunRamakrishnan DurairajanJianan JiChengjun JiaJunchen Jiang

Show All Co-Authors (21)

Zaoxing Liu

Affiliation

University of Maryland

College Park

MD, USA

Publication Topics

Hash Function,
API Calls,
Approximate Entropy,
Attack Scenarios,
Autoencoder Model,
Baseline Algorithms,
Change Detection,
Combined Field,
Congested,
Continuous Features,
Data Processing,
Data Streams

Biography

Zaoxing Liu received the Ph.D. degree in computer science from Johns Hopkins University. He is currently an Assistant Professor of electrical and computer engineering and computer science with Boston University (BU). Prior to BU, he held a post-doctoral position with Carnegie Mellon University. His research has won interdisciplinary recognitions, including USENIX FAST Best Paper Award, USENIX ATC “Best of Rest,” and ACM STOC “Best of Rest.”(Based on document published on 5 April 2023).

Publications

4

Citations

4

Publications by Year

20232025

Co-Authors:

Ayse K. Coskun
Ramakrishnan Durairajan
Jianan Ji
Chengjun Jia
Junchen Jiang

Show All Co-Authors (21)

Author's Published Works

Search History

Showing 1-11 of 11 results

Conferences (11)

Sort

Filter Results

Show

Subscribed Content

Open Access Only

Range
Single Year
Xiaobing Wang(11)
Dafeng Zhang(7)
Zhenbo Luo(4)
Yingying Jiang(4)
Shuai Liu(3)
Samsung Research China - Beijing (SRC-B), Beijing, China(2)
York University(1)
Samsung R&D Institute China, Beijing(1)
Samsung Research China - Beijing (SRC-B)(1)
Beijing National Research Center for Information Science and Technology, China(1)
2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)(2)
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(2)
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(2)
2018 24th International Conference on Pattern Recognition (ICPR)(1)
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(1)
IEEE(11)
Kyoto, Japan(2)
Nashville, TN, USA(2)
Vancouver, BC, Canada(2)
Beijing, China(1)
Long Beach, CA, USA(1)
Convolutional Neural Network(6)
Convolutional Layers(5)
Bounding Box(4)
Optical Character Recognition(4)
Reconstruction Module(4)

Select All on Page

Sort By

Results

CLIP-Cluster: CLIP-Guided Attribute Hallucination for Face Clustering

Shuai Shen;Wanhua Li;Xiaobing Wang;Dafeng Zhang;Zhezhu Jin;Jie Zhou;Jiwen Lu

2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Year: 2023 | Conference Paper |

Cited by: Papers (2)

HTML

One of the most important yet rarely studied challenges for supervised face clustering is the large intra-class variance caused by different face attributes such as age, pose, and expression. Images of the same identity but with different face attributes usually tend to be clustered into different sub-clusters. For the first time, we proposed an attribute hallucination framework named CLIP-Cluster...Show More

CLIP-Cluster: CLIP-Guided Attribute Hallucination for Face Clustering

Shuai Shen;Wanhua Li;Xiaobing Wang;Dafeng Zhang;Zhezhu Jin;Jie Zhou;Jiwen Lu

2023 IEEE/CVF International Conference on Computer Vision (ICCV)

Year: 2023 | Conference Paper |

MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Results

Yuekun Dai;Chongyi Li;Shangchen Zhou;Ruicheng Feng;Qingpeng Zhu;Qianhui Sun;Wenxiu Sun;Chen Change Loy;Jinwei Gu;Shuai Liu;Hao Wang;Chaoyu Feng;Luyang Wang;Guangqi Shao;Chenguang Zhang;Xiaotao Wang;Lei Lei;Dafeng Zhang;Xiangyu Kong;Guanqun Liu;Mengmeng Bai;Jia Ouyang;Xiaobing Wang;Jiahui Yuan;Xinpeng Li;Chengzhi Jiang;Ting Jiang;Wenjie Lin;Qi Wu;Mingyan Han;Jinting Luo;Lei Yu;Haoqiang Fan;Shuaicheng Liu;Bo Yan;Zhuang Li;Yadong Li;Hongbin Wang;Soonyong Song;Minghan Fu;Rayyan Azam Khan;Fangxiang Wu;Zhao Zhang;Suiyi Zhao;Huan Zheng;Yangcheng Gao;Yanyan Wei;Jiahuan Ren;Bo Wang;Yan Luo;Shuaibo Gao;Wenhui Wu;Sicong Kang;Nikhil Akalwadi;Ankit Raichur;Vinod Patil;Allabakash G;Swaroop A;Amogh Joshi;Chaitra Desai;Ramesh Ashok Tabib;Ujwala Patil;Uma Mudenagudi Sicheng Li;Ruoxi Zhu;Jiazheng Lian;Shusong Xu;Zihao Liu;Sabari Nathan;Priya Kansal

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

Year: 2023 | Conference Paper |

Cited by: Papers (8)

HTML

Developing and integrating advanced image sensors with novel algorithms in camera systems are prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging...Show More

MIPI 2023 Challenge on Nighttime Flare Removal: Methods and Results

Yuekun Dai;Chongyi Li;Shangchen Zhou;Ruicheng Feng;Qingpeng Zhu;Qianhui Sun;Wenxiu Sun;Chen Change Loy;Jinwei Gu;Shuai Liu;Hao Wang;Chaoyu Feng;Luyang Wang;Guangqi Shao;Chenguang Zhang;Xiaotao Wang;Lei Lei;Dafeng Zhang;Xiangyu Kong;Guanqun Liu;Mengmeng Bai;Jia Ouyang;Xiaobing Wang;Jiahui Yuan;Xinpeng Li;Chengzhi Jiang;Ting Jiang;Wenjie Lin;Qi Wu;Mingyan Han;Jinting Luo;Lei Yu;Haoqiang Fan;Shuaicheng Liu;Bo Yan;Zhuang Li;Yadong Li;Hongbin Wang;Soonyong Song;Minghan Fu;Rayyan Azam Khan;Fangxiang Wu;Zhao Zhang;Suiyi Zhao;Huan Zheng;Yangcheng Gao;Yanyan Wei;Jiahuan Ren;Bo Wang;Yan Luo;Shuaibo Gao;Wenhui Wu;Sicong Kang;Nikhil Akalwadi;Ankit Raichur;Vinod Patil;Allabakash G;Swaroop A;Amogh Joshi;Chaitra Desai;Ramesh Ashok Tabib;Ujwala Patil;Uma Mudenagudi Sicheng Li;Ruoxi Zhu;Jiazheng Lian;Shusong Xu;Zihao Liu;Sabari Nathan;Priya Kansal

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

Year: 2023 | Conference Paper |

FF-Former: Swin Fourier Transformer for Nighttime Flare Removal

Dafeng Zhang;Jia Ouyang;Guanqun Liu;Xiaobing Wang;Xiangyu Kong;Zhezhu Jin

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

Year: 2023 | Conference Paper |

Cited by: Papers (4)

HTML

In the process of removing nighttime flare, it is crucial to have a large receptive field due to the fact that flare can occupy a substantial portion of an image, even potentially the entire image. However, the conventional window-based Transformer approaches restrict the receptive field within the window, limiting its ability to capture global features. And the flare can cause the dark regions to...Show More

FF-Former: Swin Fourier Transformer for Nighttime Flare Removal

Dafeng Zhang;Jia Ouyang;Guanqun Liu;Xiaobing Wang;Xiangyu Kong;Zhezhu Jin

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

Year: 2023 | Conference Paper |

MRNET: Multi-Refinement Network for Dual-Pixel Images Defocus Deblurring

Dafeng Zhang;Xiaobing Wang;Zhezhu Jin

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

Year: 2023 | Conference Paper |

Cited by: Papers (1)

HTML

Defocus blurring is an inevitable phenomenon in cameras. Though many methods have been proposed, the problem is still challenging because of their low deblurring performance and long processing time. To solve this problem, we propose an efficient Multi-Refinement Network (MRNet) for dual-pixel images defocus deblurring. The MRNet contains two core modules that are alignment module and reconstructi...Show More

MRNET: Multi-Refinement Network for Dual-Pixel Images Defocus Deblurring

Dafeng Zhang;Xiaobing Wang;Zhezhu Jin

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

Year: 2023 | Conference Paper |

Dynamic Multi-Scale Network for Dual-Pixel Images Defocus Deblurring with Transformer

Dafeng Zhang;Xiaobing Wang

2022 IEEE International Conference on Multimedia and Expo (ICME)

Year: 2022 | Conference Paper |

Cited by: Papers (9)

HTML

Recent works achieve excellent results in dual-pixel defo-cus deblurring task by using convolutional neural network (CNN), while the scarcity of data limits the exploration and attempt of vision transformer in this task. In this paper, we propose a dynamic multi-scale network, named DMT-Net, for dual-pixel images defocus deblurring. In DMTNet, the feature extraction module is composed of several v...Show More

Dynamic Multi-Scale Network for Dual-Pixel Images Defocus Deblurring with Transformer

Dafeng Zhang;Xiaobing Wang

2022 IEEE International Conference on Multimedia and Expo (ICME)

Year: 2022 | Conference Paper |

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)

HTML

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 |

NTIRE 2021 Challenge on Image Deblurring

Seungjun Nah;Sanghyun Son;Suyoung Lee;Radu Timofte;Kyoung Mu Lee;Liangyu Chen;Jie Zhang;Xin Lu;Xiaojie Chu;Chengpeng Chen;Zhiwei Xiong;Ruikang Xu;Zeyu Xiao;Jie Huang;Yueyi Zhang;Si Xi;Jia Wei;Haoran Bai;Songsheng Cheng;Hao Wei;Long Sun;Jinhui Tang;Jinshan Pan;Donghyeon Lee;Chulhee Lee;Taesung Kim;Xiaobing Wang;Dafeng Zhang;Zhihong Pan;Tianwei Lin;Wenhao Wu;Dongliang He;Baopu Li;Boyun Li;Teng Xi;Gang Zhang;Jingtuo Liu;Junyu Han;Errui Ding;Guangpin Tao;Wenqing Chu;Yun Cao;Donghao Luo;Ying Tai;Tong Lu;Chengjie Wang;Jilin Li;Feiyue Huang;Hanting Chen;Shuaijun Chen;Tianyu Guo;Yunhe Wang;Syed Waqas Zamir;Aditya Arora;Salman Khan;Munawar Hayat;Fahad Shahbaz Khan;Ling Shao;Yushen Zuo;Yimin Ou;Yuanjun Chai;Lei Shi;Shuai Liu;Lei Lei;Chaoyu Feng;Kai Zeng;Yuying Yao;Xinran Liu;Zhizhou Zhang;Huacheng Huang;Yunchen Zhang;Mingchao Jiang;Wenbin Zou;Si Miao;Yangwoo Kim;Yuejin Sun;Senyou Deng;Wenqi Ren;Xiaochun Cao;Tao Wang;Maitreya Suin;A. N. Rajagopalan;Vinh Van Duong;Thuc Huu Nguyen;Jonghoon Yim;Byeungwoo Jeon;Ru Li;Junwei Xie;Jong-Wook Han;Jun-Ho Choi;Jun-Hyuk Kim;Jong-Seok Lee;Jiaxin Zhang;Fan Peng;David Svitov;Dmitry Pakulich;Jaeyeob Kim;Jechang Jeong

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

Year: 2021 | Conference Paper |

Cited by: Papers (35)

HTML

Motion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation. This paper reviews the NTIRE 2021 Challenge on Image Deblurring. In this challenge report, we describe the challenge specifics and the evaluation results from the 2 competition tracks with the proposed solutions. While both the tracks aim to recover a high-quality ...Show More

NTIRE 2021 Challenge on Image Deblurring

Seungjun Nah;Sanghyun Son;Suyoung Lee;Radu Timofte;Kyoung Mu Lee;Liangyu Chen;Jie Zhang;Xin Lu;Xiaojie Chu;Chengpeng Chen;Zhiwei Xiong;Ruikang Xu;Zeyu Xiao;Jie Huang;Yueyi Zhang;Si Xi;Jia Wei;Haoran Bai;Songsheng Cheng;Hao Wei;Long Sun;Jinhui Tang;Jinshan Pan;Donghyeon Lee;Chulhee Lee;Taesung Kim;Xiaobing Wang;Dafeng Zhang;Zhihong Pan;Tianwei Lin;Wenhao Wu;Dongliang He;Baopu Li;Boyun Li;Teng Xi;Gang Zhang;Jingtuo Liu;Junyu Han;Errui Ding;Guangpin Tao;Wenqing Chu;Yun Cao;Donghao Luo;Ying Tai;Tong Lu;Chengjie Wang;Jilin Li;Feiyue Huang;Hanting Chen;Shuaijun Chen;Tianyu Guo;Yunhe Wang;Syed Waqas Zamir;Aditya Arora;Salman Khan;Munawar Hayat;Fahad Shahbaz Khan;Ling Shao;Yushen Zuo;Yimin Ou;Yuanjun Chai;Lei Shi;Shuai Liu;Lei Lei;Chaoyu Feng;Kai Zeng;Yuying Yao;Xinran Liu;Zhizhou Zhang;Huacheng Huang;Yunchen Zhang;Mingchao Jiang;Wenbin Zou;Si Miao;Yangwoo Kim;Yuejin Sun;Senyou Deng;Wenqi Ren;Xiaochun Cao;Tao Wang;Maitreya Suin;A. N. Rajagopalan;Vinh Van Duong;Thuc Huu Nguyen;Jonghoon Yim;Byeungwoo Jeon;Ru Li;Junwei Xie;Jong-Wook Han;Jun-Ho Choi;Jun-Hyuk Kim;Jong-Seok Lee;Jiaxin Zhang;Fan Peng;David Svitov;Dmitry Pakulich;Jaeyeob Kim;Jechang Jeong

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

Year: 2021 | Conference Paper |

Arbitrary Shape Scene Text Detection With Adaptive Text Region Representation

Xiaobing Wang;Yingying Jiang;Zhenbo Luo;Cheng-Lin Liu;Hyunsoo Choi;Sungjin Kim

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

Year: 2019 | Conference Paper |

Cited by: Papers (136)

HTML

Scene text detection attracts much attention in computer vision, because it can be widely used in many applications such as real-time text translation, automatic information entry, blind person assistance, robot sensing and so on. Though many methods have been proposed for horizontal and oriented texts, detecting irregular shape texts such as curved texts is still a challenging problem. To solve t...Show More

Arbitrary Shape Scene Text Detection With Adaptive Text Region Representation

Xiaobing Wang;Yingying Jiang;Zhenbo Luo;Cheng-Lin Liu;Hyunsoo Choi;Sungjin Kim

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

Year: 2019 | Conference Paper |

R2 CNN: Rotational Region CNN for Arbitrarily-Oriented Scene Text Detection

Yingying Jiang;Xiangyu Zhu;Xiaobing Wang;Shuli Yang;Wei Li;Hua Wang;Pei Fu;Zhenbo Luo

2018 24th International Conference on Pattern Recognition (ICPR)

Year: 2018 | Conference Paper |

Cited by: Papers (204)

HTML

Scene text detection is challenging as the input may have different orientations, sizes, font styles, lighting conditions, perspective distortions and languages. This paper addresses the problem by designing a Rotational Region CNN (R2CNN). R2CNN includes a Text Region Proposal Network (Text-RPN) to estimate approximate text regions and a multitask refinement network to get the precise inclined bo...Show More

R2 CNN: Rotational Region CNN for Arbitrarily-Oriented Scene Text Detection

Yingying Jiang;Xiangyu Zhu;Xiaobing Wang;Shuli Yang;Wei Li;Hua Wang;Pei Fu;Zhenbo Luo

2018 24th International Conference on Pattern Recognition (ICPR)

Year: 2018 | Conference Paper |

Deep Residual Text Detection Network for Scene Text

Xiangyu Zhu;Yingying Jiang;Shuli Yang;Xiaobing Wang;Wei Li;Pei Fu;Hua Wang;Zhenbo Luo

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)

Year: 2017 | Conference Paper |

Cited by: Papers (13)

HTML

Scene text detection is a challenging problem in computer vision. In this paper, we propose a novel text detection network based on prevalent object detection frameworks. In order to obtain stronger semantic feature, we adopt ResNet as feature extraction layers and exploit multi-level feature by combining hierarchical convolutional networks. A vertical proposal mechanism is utilized to avoid propo...Show More

Deep Residual Text Detection Network for Scene Text

Xiangyu Zhu;Yingying Jiang;Shuli Yang;Xiaobing Wang;Wei Li;Pei Fu;Hua Wang;Zhenbo Luo

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)

Year: 2017 | Volume: 01 | Conference Paper |

End-to-End Scene Text Recognition in Videos Based on Multi Frame Tracking

Xiaobing Wang;Yingying Jiang;Shuli Yang;Xiangyu Zhu;Wei Li;Pei Fu;Hua Wang;Zhenbo Luo

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)

Year: 2017 | Conference Paper |

Cited by: Papers (16)

HTML

Text detection and recognition in scene images and videos attract much attention in computer vision recently. However, most existing text detection and recognition methods only focus on static images. In this paper an end-to-end scene text recognition method based on multi frame tracking is proposed for text in videos, in which temporal information is employed to improve performance. First, an end...Show More

End-to-End Scene Text Recognition in Videos Based on Multi Frame Tracking

Xiaobing Wang;Yingying Jiang;Shuli Yang;Xiangyu Zhu;Wei Li;Pei Fu;Hua Wang;Zhenbo Luo

2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)

Year: 2017 | Volume: 01 | Conference Paper |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Test Whats new message.