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CASIA OpenIR
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Learning Explicit Contact for Implicit Reconstruction of Hand-Held Objects from Monocular Images 会议论文
AAAI Technical Track on Computer Vision II, Vancouver, Canada, February 22 – February 25, 2024
作者:  Junxing Hu;  Hongwen Zhang;  Zerui Chen;  Mengcheng Li;  Yunlong Wang;  Yebin Liu;  Zhenan Sun
Adobe PDF(1483Kb)  |  收藏  |  浏览/下载：31/12  |  提交时间：2024/05/30
Sensing Micro-Motion Human Patterns using Multimodal mmRadar and Video Signal for Affective and Psychological Intelligence 会议论文
, Canada, 2023-10
作者:  Ru, Yiwei;  Li, Peipei;  Sun, Muyi;  Wang, Yunlong;  Zhang, Kunbo;  Li, Qi;  He, Zhaofeng;  Sun, Zhenan
Adobe PDF(8050Kb)  |  收藏  |  浏览/下载：184/53  |  提交时间：2024/02/23
End-to-end view synthesis for light field imaging with pseudo 4DCNN 会议论文
Proceedings of the european conference on computer vision (ECCV), 德国慕尼黑, 2018.09.08-2018.09.14
作者:  Wang YL(王云龙);  Liu F(刘菲);  Wang ZL(王子磊);  Hou GQ(侯广琦);  Sun ZN(孙哲南);  Tan TN(谭铁牛)
Adobe PDF(3226Kb)  |  收藏  |  浏览/下载：89/37  |  提交时间：2023/08/15
A Novel Deep-learning Pipeline for Light Field Image Based Material Recognition 会议论文
, Milan, Italy, 10-15 Jan. 2021
作者:  Wang, Yunlong;  Zhang, Kunbo;  Sun, Zhenan
Adobe PDF(3558Kb)  |  收藏  |  浏览/下载：279/68  |  提交时间：2021/10/08
High-fidelity View Synthesis for Light Field Imaging With Extended Pseudo 4DCNN 期刊论文
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2020, 卷号: 6, 页码: 830-842
作者:  Wang, Yunlong;  Liu, Fei;  Zhang, Kunbo;  Wang, Zilei;  Sun, Zhenan;  Tan, Tieniu
Adobe PDF(7054Kb)  |  收藏  |  浏览/下载：210/40  |  提交时间：2020/09/28
View synthesis  light field reconstruction  end-to-end  structure preserving  extended pseudo 4DCNN  
LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 卷号: 27, 期号: 9, 页码: 4274-4286
作者:  Wang, Yunlong;  Liu, Fei;  Zhang, Kunbo;  Hou, Guangqi;  Sun, Zhenan;  Tan, Tieniu
Adobe PDF(4648Kb)  |  收藏  |  浏览/下载：359/28  |  提交时间：2018/10/10
Implicitly Multi-scale Fusion  Bidirectional Recurrent Convolutional Neural Network  Light-field  Super-resolution