Wenbo Wang - IEEE Xplore Author Profile

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Author details

Wenbo Wang

Publications

3

Citations

3

Publications by Year

20232024

Co-Authors:

Liangzhu ChengShujing FangFei HuiXin JinZiqi Li

Show All Co-Authors (11)

Wenbo Wang

Affiliation

School of Information Engineering

Chang’an University

Xi’an, China

Publication Topics

Autonomous Vehicles,
Actor Network,
Critic Network,
Deep Learning,
Deep Reinforcement Learning,
Long Short-term Memory,
Reward Function,
Trajectory Planning,
Vehicle State,
Anthropomorphic,
Artificial Potential Field,
Attention Mechanism

Biography

Wenbo Wang received the M.S. degree in motors and appliances from Xidian University, Xi'an, China, in 2018. He is currently working toward the Ph.D. degree in traffic information engineering and control with the School of Information Engineering, Chang'an University, Xi'an. His research interests include driving behavior modeling, trajectory planning, connected and automated electric vehicles, and data-driven traffic flow analysis.(Based on document published on 17 June 2024).

Publications

3

Citations

3

Publications by Year

20232024

Co-Authors:

Liangzhu Cheng
Shujing Fang
Fei Hui
Xin Jin
Ziqi Li

Show All Co-Authors (11)

Author's Published Works

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Showing 1-10 of 10 results

Conferences (7)

Journals (2)

Early Access Articles (1)

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Wentao Chao(10)
Fuqing Duan(9)
Xuechun Wang(7)
Guanghui Wang(7)
Yingqian Wang(5)
School of Artificial Intelligence, Beijing Normal University, Beijing, China(4)
Department of Computer Science, Toronto Metropolitan University, Toronto, ON, Canada(2)
College of Electronic Science and Technology, National University of Defense Technology, Changsha, China(2)
State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, and Beihang Hangzhou Innovation Institute Yuhang(1)
Toronto Metropolitan University(1)
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(2)
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(2)
IEEE Transactions on Computational Imaging(2)
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
2022 IEEE International Conference on Image Processing (ICIP)(1)
IEEE(10)
Media(2)
Seattle, WA, USA(2)
Vancouver, BC, Canada(2)
Bordeaux, France(1)
Nashville, TN, USA(1)
Niagara Falls, ON, Canada(1)
Light Field(7)
Depth Estimation(5)
Convolutional Neural Network(4)
L1 Loss(4)
Light Field Images(4)

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Results

MaskBlur: Spatial and Angular Data Augmentation for Light Field Image Super-Resolution

Wentao Chao;Fuqing Duan;Yulan Guo;Guanghui Wang

IEEE Transactions on Multimedia

Year: 2024 | Early Access Article |

Data augmentation (DA) is an effective approach for enhancing model performance with limited data, such as light field (LF) image super-resolution (SR). LF images inherently possess rich spatial and angular information. Nonetheless, there is a scarcity of DA methodologies explicitly tailored for LF images, and existing works tend to concentrate solely on either the spatial or angular domain. This ...Show More

MaskBlur: Spatial and Angular Data Augmentation for Light Field Image Super-Resolution

Wentao Chao;Fuqing Duan;Yulan Guo;Guanghui Wang

IEEE Transactions on Multimedia

Year: 2024 | Early Access Article |

OccCasNet: Occlusion-Aware Cascade Cost Volume for Light Field Depth Estimation

Wentao Chao;Fuqing Duan;Xuechun Wang;Yingqian Wang;Ke Lu;Guanghui Wang

IEEE Transactions on Computational Imaging

Year: 2024 | Volume: 10 | Journal Article |

Cited by: Papers (2)

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Depth estimation using the Light Field (LF) technique is an essential task with a wide range of practical applications. While mainstream approaches based on multi-view stereo techniques can attain exceptional accuracy by creating finer cost volumes, they are resource-intensive, time-consuming, and often overlook occlusion during cost volume construction. To address these issues and strike a better...Show More

OccCasNet: Occlusion-Aware Cascade Cost Volume for Light Field Depth Estimation

Wentao Chao;Fuqing Duan;Xuechun Wang;Yingqian Wang;Ke Lu;Guanghui Wang

IEEE Transactions on Computational Imaging

Year: 2024 | Volume: 10 | Journal Article |

Point Cloud Reconstruction Optimization of Light Field Image based on Intra-class Distance

Xuechun Wang;Wentao Chao;Fuqing Duan

2024 IEEE International Conference on Multimedia and Expo (ICME)

Year: 2024 | Conference Paper |

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A single light field image, containing multiple views, can be utilized in conjunction with estimated depth map to generate three-dimensional (3D) point cloud. It is noteworthy that many depth estimation algorithms frequently produce depth maps plagued by issues such as holes and blurred edges. Many algorithms use global optimization directly to optimize depth maps without considering the effects o...Show More

Point Cloud Reconstruction Optimization of Light Field Image based on Intra-class Distance

Xuechun Wang;Wentao Chao;Fuqing Duan

2024 IEEE International Conference on Multimedia and Expo (ICME)

Year: 2024 | Conference Paper |

NTIRE 2024 Challenge on Light Field Image Super-Resolution: Methods and Results

Yingqian Wang;Zhengyu Liang;Qianyu Chen;Longguang Wang;Jungang Yang;Radu Timofte;Yulan Guo;Wentao Chao;Yiming Kan;Xuechun Wang;Fuqing Duan;Guanghui Wang;Wang Xia;Ziqi Wang;Yue Yan;Peiqi Xia;Shunzhou Wang;Yao Lu;Angulia Yang;Kai Jin;Zeqiang Wei;Sha Guo;Mingzhi Gao;Xiuzhuang Zhou;Zhongxin Yu;Shaofei Luo;Cheng Zhong;Shaorui Chen;Long Peng;Yuhong He;Gaosheng Liu;Huanjing Yue;Jingyu Yang;Zhengjian Yao;Jiakui Hu;Lujia Jin;Zhi-Song Liu;Chenhang He;Jun Xiao;Xiuyuan Wang;Zonglin Tian;Yifan Mao;Deyang Liu;Shizheng Li;Ping An

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

Year: 2024 | Conference Paper |

Cited by: Papers (22)

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In this report, we summarize the 2nd NTIRE challenge on light field (LF) image super-resolution (SR) with a focus on new methods and results. This challenge aims at superresolving LF images under the standard bicubic downsampling degradation with a magnification factor of ×4. Compared with single image SR, the major challenge of LF image SR lies in how to exploit complementary angular information ...Show More

NTIRE 2024 Challenge on Light Field Image Super-Resolution: Methods and Results

Yingqian Wang;Zhengyu Liang;Qianyu Chen;Longguang Wang;Jungang Yang;Radu Timofte;Yulan Guo;Wentao Chao;Yiming Kan;Xuechun Wang;Fuqing Duan;Guanghui Wang;Wang Xia;Ziqi Wang;Yue Yan;Peiqi Xia;Shunzhou Wang;Yao Lu;Angulia Yang;Kai Jin;Zeqiang Wei;Sha Guo;Mingzhi Gao;Xiuzhuang Zhou;Zhongxin Yu;Shaofei Luo;Cheng Zhong;Shaorui Chen;Long Peng;Yuhong He;Gaosheng Liu;Huanjing Yue;Jingyu Yang;Zhengjian Yao;Jiakui Hu;Lujia Jin;Zhi-Song Liu;Chenhang He;Jun Xiao;Xiuyuan Wang;Zonglin Tian;Yifan Mao;Deyang Liu;Shizheng Li;Ping An

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

Year: 2024 | Conference Paper |

BigEPIT: Scaling EPIT for Light Field Image Super-Resolution

Wentao Chao;Yiming Kan;Xuechun Wang;Fuqing Duan;Guanghui Wang

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

Year: 2024 | Conference Paper |

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Existing methods have been developed for light field (LF) image Super-Resolution (SR) and achieved continuously improved performance while suffering a significant performance drop when handling scenes with large disparity variations. EPIT [1] was proposed to mitigate the disparity issue through non-local spatial-angular correlation learning. However EPIT has limitations due to the limited scale of...Show More

BigEPIT: Scaling EPIT for Light Field Image Super-Resolution

Wentao Chao;Yiming Kan;Xuechun Wang;Fuqing Duan;Guanghui Wang

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

Year: 2024 | Conference Paper |

Learning Sub-Pixel Disparity Distribution for Light Field Depth Estimation

Wentao Chao;Xuechun Wang;Yingqian Wang;Guanghui Wang;Fuqing Duan

IEEE Transactions on Computational Imaging

Year: 2023 | Volume: 9 | Journal Article |

Cited by: Papers (19)

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Light field (LF) depth estimation plays a crucial role in many LF-based applications. Existing LF depth estimation methods consider depth estimation as a regression problem, where a pixel-wise L1 loss is employed to supervise the training process. However, the disparity map is only a sub-space projection (i.e., an expectation) of the disparity distribution, which is essential for models to learn. ...Show More

Learning Sub-Pixel Disparity Distribution for Light Field Depth Estimation

Wentao Chao;Xuechun Wang;Yingqian Wang;Guanghui Wang;Fuqing Duan

IEEE Transactions on Computational Imaging

Year: 2023 | Volume: 9 | Journal Article |

LFNAT 2023 Challenge on Light Field Depth Estimation: Methods and Results

Hao Sheng;Yebin Liu;Jingyi Yu;Gaochang Wu;Wei Xiong;Ruixuan Cong;Rongshan Chen;Longzhao Guo;Yanlin Xie;Shuo Zhang;Song Chang;Youfang Lin;Wentao Chao;Xuechun Wang;Guanghui Wang;Fuqing Duan;Tun Wang;Da Yang;Zhenglong Cui;Sizhe Wang;Mingyuan Zhao;Qiong Wang;Qianyu Chen;Zhengyu Liang;Yingqian Wang;Jungang Yang;Xueting Yang;Junli Deng

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

Year: 2023 | Conference Paper |

Cited by: Papers (10)

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This paper reviews the 1st LFNAT challenge on light field depth estimation, which aims at predicting disparity information of central view image in a light field (i.e., pixel offset between central view image and adjacent view image). Compared to multi-view stereo matching, light field depth estimation emphasizes efficient utilization of the 2D angular information from multiple regularly varying v...Show More

LFNAT 2023 Challenge on Light Field Depth Estimation: Methods and Results

Hao Sheng;Yebin Liu;Jingyi Yu;Gaochang Wu;Wei Xiong;Ruixuan Cong;Rongshan Chen;Longzhao Guo;Yanlin Xie;Shuo Zhang;Song Chang;Youfang Lin;Wentao Chao;Xuechun Wang;Guanghui Wang;Fuqing Duan;Tun Wang;Da Yang;Zhenglong Cui;Sizhe Wang;Mingyuan Zhao;Qiong Wang;Qianyu Chen;Zhengyu Liang;Yingqian Wang;Jungang Yang;Xueting Yang;Junli Deng

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

Year: 2023 | Conference Paper |

NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results

Yingqian Wang;Longguang Wang;Zhengyu Liang;Jungang Yang;Radu Timofte;Yulan Guo;Kai Jin;Zeqiang Wei;Angulia Yang;Sha Guo;Mingzhi Gao;Xiuzhuang Zhou;Vinh Van Duong;Thuc Nguyen Huu;Jonghoon Yim;Byeungwoo Jeon;Yutong Liu;Zhen Cheng;Zeyu Xiao;Ruikang Xu;Zhiwei Xiong;Gaosheng Liu;Manchang Jin;Huanjing Yue;Jingyu Yang;Chen Gao;Shuo Zhang;Song Chang;Youfang Lin;Wentao Chao;Xuechun Wang;Guanghui Wang;Fuqing Duan;Wang Xia;Yan Wang;Peiqi Xia;Shunzhou Wang;Yao Lu;Ruixuan Cong;Hao Sheng;Da Yang;Rongshan Chen;Sizhe Wang;Zhenglong Cui;Yilei Chen;Yongjie Lu;Dongjun Cai;Ping An;Ahmed Salem;Hatem Ibrahem;Bilel Yagoub;Hyun-Soo Kang;Zekai Zeng;Heng Wu

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

Year: 2023 | Conference Paper |

Cited by: Papers (33)

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In this report, we summarize the first NTIRE challenge on light field (LF) image super-resolution (SR), which aims at super-resolving LF images under the standard bicubic degradation with a magnification factor of 4. This challenge develops a new LF dataset called NTIRE-2023 for validation and test, and provides a toolbox called BasicLFSR to facilitate model development. Compared with single image...Show More

NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results

Yingqian Wang;Longguang Wang;Zhengyu Liang;Jungang Yang;Radu Timofte;Yulan Guo;Kai Jin;Zeqiang Wei;Angulia Yang;Sha Guo;Mingzhi Gao;Xiuzhuang Zhou;Vinh Van Duong;Thuc Nguyen Huu;Jonghoon Yim;Byeungwoo Jeon;Yutong Liu;Zhen Cheng;Zeyu Xiao;Ruikang Xu;Zhiwei Xiong;Gaosheng Liu;Manchang Jin;Huanjing Yue;Jingyu Yang;Chen Gao;Shuo Zhang;Song Chang;Youfang Lin;Wentao Chao;Xuechun Wang;Guanghui Wang;Fuqing Duan;Wang Xia;Yan Wang;Peiqi Xia;Shunzhou Wang;Yao Lu;Ruixuan Cong;Hao Sheng;Da Yang;Rongshan Chen;Sizhe Wang;Zhenglong Cui;Yilei Chen;Yongjie Lu;Dongjun Cai;Ping An;Ahmed Salem;Hatem Ibrahem;Bilel Yagoub;Hyun-Soo Kang;Zekai Zeng;Heng Wu

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

Year: 2023 | Conference Paper |

DEKRV2: More Accurate or Fast than DEKR

Wentao Chao;Fuqing Duan;Peng Du;Wanning Zhu;Tianyuan Jia;Deqi Li

2022 IEEE International Conference on Image Processing (ICIP)

Year: 2022 | Conference Paper |

Cited by: Papers (2)

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Bottom-up human pose estimation has raised more investigation in recent years, especially 2D keypoints regression. However, the state-of-art DEKR [1] still has some aspects (e.g., speed and accuracy) to be improved. In this paper, we propose a new framework named DEKRv2, which has been enhanced compared to DEKR. When DEKR calculates the offset of each keypoint, it only considers the features of th...Show More

DEKRV2: More Accurate or Fast than DEKR

Wentao Chao;Fuqing Duan;Peng Du;Wanning Zhu;Tianyuan Jia;Deqi Li

2022 IEEE International Conference on Image Processing (ICIP)

Year: 2022 | Conference Paper |

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Ren Yang;Radu Timofte;Jing Liu;Yi Xu;Xinjian Zhang;Minyi Zhao;Shuigeng Zhou;Kelvin C.K. Chan;Shangchen Zhou;Xiangyu Xu;Chen Change Loy;Xin Li;Fanglong Liu;He Zheng;Lielin Jiang;Qi Zhang;Dongliang He;Fu Li;Qingqing Dang;Yibin Huang;Matteo Maggioni;Zhongqian Fu;Shuai Xiao;Cheng Li;Thomas Tanay;Fenglong Song;Wentao Chao;Qiang Guo;Yan Liu;Jiang Li;Xiaochao Qu;Dewang Hou;Jiayu Yang;Lyn Jiang;Di You;Zhenyu Zhang;Chong Mou;Iaroslav Koshelev;Pavel Ostyakov;Andrey Somov;Jia Hao;Xueyi Zou;Shijie Zhao;Xiaopeng Sun;Yiting Liao;Yuanzhi Zhang;Qing Wang;Gen Zhan;Mengxi Guo;Junlin Li;Ming Lu;Zhan Ma;Pablo Navarrete Michelini;Hai Wang;Yiyun Chen;Jingyu Guo;Liliang Zhang;Wenming Yang;Sijung Kim;Syehoon Oh;Yucong Wang;Minjie Cai;Wei Hao;Kangdi Shi;Liangyan Li;Jun Chen;Wei Gao;Wang Liu;Xiaoyu Zhang;Linjie Zhou;Sixin Lin;Ru Wang

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 reviews the first NTIRE challenge on quality enhancement of compressed video, with focus on proposed solutions and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks. Tracks 1 and 2 aim at enhancing the videos compressed by HEVC at a fixed QP, while Track 3 is de-signed for enhancing the videos compressed by x265 at a ...Show More

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

Ren Yang;Radu Timofte;Jing Liu;Yi Xu;Xinjian Zhang;Minyi Zhao;Shuigeng Zhou;Kelvin C.K. Chan;Shangchen Zhou;Xiangyu Xu;Chen Change Loy;Xin Li;Fanglong Liu;He Zheng;Lielin Jiang;Qi Zhang;Dongliang He;Fu Li;Qingqing Dang;Yibin Huang;Matteo Maggioni;Zhongqian Fu;Shuai Xiao;Cheng Li;Thomas Tanay;Fenglong Song;Wentao Chao;Qiang Guo;Yan Liu;Jiang Li;Xiaochao Qu;Dewang Hou;Jiayu Yang;Lyn Jiang;Di You;Zhenyu Zhang;Chong Mou;Iaroslav Koshelev;Pavel Ostyakov;Andrey Somov;Jia Hao;Xueyi Zou;Shijie Zhao;Xiaopeng Sun;Yiting Liao;Yuanzhi Zhang;Qing Wang;Gen Zhan;Mengxi Guo;Junlin Li;Ming Lu;Zhan Ma;Pablo Navarrete Michelini;Hai Wang;Yiyun Chen;Jingyu Guo;Liliang Zhang;Wenming Yang;Sijung Kim;Syehoon Oh;Yucong Wang;Minjie Cai;Wei Hao;Kangdi Shi;Liangyan Li;Jun Chen;Wei Gao;Wang Liu;Xiaoyu Zhang;Linjie Zhou;Sixin Lin;Ru Wang

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

Year: 2021 | Conference Paper |

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