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26 results on '"Cui, Zhenglong"'

5. LF-DWNet: Robust Depth Estimation Network for Light Field with Disparity Warping

Author

Zhao, Yuxin, Cui, Zhenglong, Chen, Rongshan, Yang, Da, Sheng, Hao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wang, Lei, editor, Segal, Michael, editor, Chen, Jenhui, editor, and Qiu, Tie, editor

Published
2022
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14. NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results

Author

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

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

Author

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

Published
2023
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18. An Occlusion and Noise-Aware Stereo Framework Based on Light Field Imaging for Robust Disparity Estimation

Author

Yang, Da, Cui, Zhenglong, Sheng, Hao, Chen, Rongshan, Cong, Ruixuan, Wang, Shuai, and Xiong, Zhang

Abstract

Stereo vision is widely studied for depth information extraction. However, occlusion and noise pose significant challenges to traditional methods due to failure in photo consistency. In this paper, an occlusion and noise-aware stereo framework named ONAF is proposed to get a robust depth estimation by integrating the advantages of correspondence cues and refocusing cues from light field (LF). ONAF consists of two special depth cue extractors: correspondence depth cue extractor (CCE) and refocusing depth cue extractor (RCE). CCE extracts accurate correspondence depth cues in occlusion areas based on multi-direction Ray-Epipolar Plane Images (Ray-EPIs) from LF, which are more robust than traditional multi-direction EPIs. RCE generates accurate refocusing depth cues in noise areas, benefitting from the many-to-one integration strategy and the directional perception of texture and occlusion based on multi-direction focal stacks from LF. Attention mechanism is introduced to complementarily fuse CCE and RCE to generate optimum depth maps. The experimental results prove the effectiveness of ONAF, which outperforms state-of-the-art disparity estimation methods, especially in occlusion and noise areas.

Published
2024
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26. Effect of Recycled Coarse Aggregate Suction and Drainage on Drying Shrinkage of Concrete.

Author

CUI Zhenglong and ZHANG Han

Abstract

The experiment focused on the absorption and drainage characteristics of recycled coarse aggregate. The recycled coarse aggregate bonded with strain gauges was embedded in C30 strength grade concrete, and the shrinkage strain of recycled coarse aggregate in concrete during drying shrinkage was measured directly. Based on the relationship between the strain and drainage rate of recycled coarse aggregate under different humidity conditions, the drainage characteristics of recycled coarse aggregate in concrete were calculated, and the relationship between the drainage rate of recycled coarse aggregate and the drainage rate of recycled coarse aggregate was established. The results showed that the trend line of strain and saturation curve of regenerated coarse aggregate was relatively close to that of natural coarse aggregate in the process of draining and drainage, and the strain variation caused by dry and wet of the two kinds of aggregate had a reversible trend. There was a linear relationship between the strain and the drainage rate of recycled coarse aggregate and natural aggregate. The shrinkage strain of coarse aggregate in concrete was smaller than that of specimen, and the shrinkage strains of recycled coarse aggregate and recycled concrete were larger than that of natural aggregate and concrete. The drainage rate of recycled concrete was higher than that of internal recycled coarse aggregate. [ABSTRACT FROM AUTHOR]

Published
2020
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