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Your search keyword '"Gu, Yuzhang"' showing total 5 results
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5 results on '"Gu, Yuzhang"'

1. The Ninth Visual Object Tracking VOT2021 Challenge Results

Author

Kristan, Matej, primary, Matas, Jiri, additional, Leonardis, Ales, additional, Felsberg, Michael, additional, Pflugfelder, Roman, additional, Kamarainen, Joni-Kristian, additional, Chang, Hyung Jin, additional, Danelljan, Martin, additional, Zajc, Luka Cehovin, additional, Lukezic, Alan, additional, Drbohlav, Ondrej, additional, Kapyla, Jani, additional, Hager, Gustav, additional, Yan, Song, additional, Yang, Jinyu, additional, Zhang, Zhongqun, additional, Fernandez, Gustavo, additional, Abdelpakey, Mohamed, additional, Bhat, Goutam, additional, Cerkezi, Llukman, additional, Cevikalp, Hakan, additional, Chen, Shengyong, additional, Chen, Xin, additional, Cheng, Miao, additional, Cheng, Ziyi, additional, Chiu, Yu-Chen, additional, Cirakman, Ozgun, additional, Cui, Yutao, additional, Dai, Kenan, additional, Dasari, Mohana Murali, additional, Deng, Qili, additional, Dong, Xingping, additional, Du, Daniel K., additional, Dunnhofer, Matteo, additional, Feng, Zhen-Hua, additional, Feng, Zhiyong, additional, Fu, Zhihong, additional, Ge, Shiming, additional, Gorthi, Rama Krishna, additional, Gu, Yuzhang, additional, Gunsel, Bilge, additional, Guo, Qing, additional, Gurkan, Filiz, additional, Han, Wencheng, additional, Huang, Yanyan, additional, Lawin, Felix Jaremo, additional, Jhang, Shang-Jhih, additional, Ji, Rongrong, additional, Jiang, Cheng, additional, Jiang, Yingjie, additional, Juefei-Xu, Felix, additional, Jun, Yin, additional, Ke, Xiao, additional, Khan, Fahad Shahbaz, additional, Hak Kim, Byeong, additional, Kittler, Josef, additional, Lan, Xiangyuan, additional, Lee, Jun Ha, additional, Leibe, Bastian, additional, Li, Hui, additional, Li, Jianhua, additional, Li, Xianxian, additional, Li, Yuezhou, additional, Liu, Bo, additional, Liu, Chang, additional, Liu, Jingen, additional, Liu, Li, additional, Liu, Qingjie, additional, Lu, Huchuan, additional, Lu, Wei, additional, Luiten, Jonathon, additional, Ma, Jie, additional, Ma, Ziang, additional, Martinel, Niki, additional, Mayer, Christoph, additional, Memarmoghadam, Alireza, additional, Micheloni, Christian, additional, Niu, Yuzhen, additional, Paudel, Danda, additional, Peng, Houwen, additional, Qiu, Shoumeng, additional, Rajiv, Aravindh, additional, Rana, Muhammad, additional, Robinson, Andreas, additional, Saribas, Hasan, additional, Shao, Ling, additional, Shehata, Mohamed, additional, Shen, Furao, additional, Shen, Jianbing, additional, Simonato, Kristian, additional, Song, Xiaoning, additional, Tang, Zhangyong, additional, Timofte, Radu, additional, Torr, Philip, additional, Tsai, Chi-Yi, additional, Uzun, Bedirhan, additional, Van Gool, Luc, additional, Voigtlaender, Paul, additional, Wang, Dong, additional, Wang, Guangting, additional, Wang, Liangliang, additional, Wang, Lijun, additional, Wang, Limin, additional, Wang, Linyuan, additional, Wang, Yong, additional, Wang, Yunhong, additional, Wu, Chenyan, additional, Wu, Gangshan, additional, Wu, Xiao-Jun, additional, Xie, Fei, additional, Xu, Tianyang, additional, Xu, Xiang, additional, Xue, Wanli, additional, Yan, Bin, additional, Yang, Wankou, additional, Yang, Xiaoyun, additional, Ye, Yu, additional, Yin, Jun, additional, Zhang, Chengwei, additional, Zhang, Chunhui, additional, Zhang, Haitao, additional, Zhang, Kaihua, additional, Zhang, Kangkai, additional, Zhang, Xiaohan, additional, Zhang, Xiaolin, additional, Zhang, Xinyu, additional, Zhang, Zhibin, additional, Zhao, Shaochuan, additional, Zhen, Ming, additional, Zhong, Bineng, additional, Zhu, Jiawen, additional, and Zhu, Xue-Feng, additional

Published
2021
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2. Order-Based Disparity Refinement Including Occlusion Handling for Stereo Matching.

Author

Ye, Xiaoqing, Gu, Yuzhang, Chen, Lili, Li, Jiamao, Wang, Han, and Zhang, Xiaolin

Subjects
STEREO image processing, STEREO vision (Computer science)
Abstract

Accurate stereo matching is still challenging in case of weakly textured areas, discontinuities, and occlusions. Besides, occlusion recovery is often regarded as a subordinate problem and simply handled. To obtain dense high-accuracy depth maps, this letter proposes an efficient multistep disparity refinement framework with occlusion handling. The framework is implemented by classifying the outliers into leftmost occlusions, nonborder occlusions, as well as mismatches, and employing different strategies to recover them. To recover occlusions, a filling order is specially introduced to avoid error propagation and surface decision based on local image content is performed when more than one background surface exists. The evaluations on Middlebury datasets and comparisons with other refinement algorithms show the superiority and robustness of our method. [ABSTRACT FROM AUTHOR]

Published
2017
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3. Free Space Estimation on Nonflat Plane Based on V-Disparity.

Author

Qu, Lei, Wang, Kangru, Chen, Lili, Gu, Yuzhang, and Zhang, Xiaolin

Subjects
IMAGE processing, STEREO vision (Computer science), DYNAMIC programming
Abstract

Recent progress in free space estimation provides precise segmentation between the ground and obstacles on flat plane. However, it remains challenging on nonflat plane, especially with the varying latitudinal and longitudinal slope or in the case of multiground plane. This letter presents a well-integrated framework for free space estimation in this challenge. Our approach couples an improved V-disparity with a proposed confidence map in a probabilistic fashion. The improved V-disparity representation adopts the sliding windows paradigm and a new V-disparity filter is designed. The proposed confidence map represents the ownership of pixels like occupancy grids, but is built only using the information of the disparity map. The free space estimation is implemented in the confidence map with the global optimization paradigm of dynamic programming. We demonstrate our superior performance compared to two other methods from the literature on a manually labeled dataset from KITTI's object detection benchmark. [ABSTRACT FROM PUBLISHER]

Published
2016
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4. Accurate Image-Guided Stereo Matching With Efficient Matching Cost and Disparity Refinement.

Author

Zhan, Yunlong, Gu, Yuzhang, Huang, Kui, Zhang, Cheng, and Hu, Keli

Subjects
*COMPUTER vision, *STEREO image, *STEREO image processing, *IMAGE processing, *STEREO vision (Computer science)
Abstract

Stereo matching is a challenging problem, and high-accuracy stereo matching is still required in various computer vision applications, e.g., 3-D scanning, autonomous navigation, and 3-D reconstruction. Therefore, we present a novel image-guided stereo matching algorithm, which employs the efficient combined matching cost and multistep disparity refinement, to improve the accuracy of existing local stereo matching algorithms. Different from all the other methods, we introduce a guidance image for the whole algorithm. This filter-based guidance image is generated by extracting the enhanced information from the raw stereo image. The combined matching cost consists of the novel double-RGB gradient, the improved lightweight census transform, and the image color. This cost measurement is robust against image noise and textureless regions in computing the matching cost. Furthermore, a new systemic multistep refinement process, which includes outlier classification, four-direction propagation, leftmost propagation, and an exponential step filter, is proposed to remove the outliers in the raw disparity map. Experiments on the Middlebury benchmark demonstrate our algorithm’s superior performance that it ranks first among the 158 submitted algorithms. Moreover, the proposed method is also robust on the 30 Middlebury data sets and the real-world Karlsruhe Institute of Technology and Toyota Technological Institute benchmark. [ABSTRACT FROM AUTHOR]

Published
2016
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