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AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

Sep 25, 2020
Pengxu Wei, Hannan Lu, Radu Timofte, Liang Lin, Wangmeng Zuo, Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding, Tangxin Xie, Liang Cao, Yan Zou, Yi Shen, Jialiang Zhang, Yu Jia, Kaihua Cheng, Chenhuan Wu, Yue Lin, Cen Liu, Yunbo Peng, Xueyi Zou, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Keon-Hee Ahn, Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee, Tongtong Zhao, Shanshan Zhao, Yoseob Han, Byung-Hoon Kim, JaeHyun Baek, Haoning Wu, Dejia Xu, Bo Zhou, Wei Guan, Xiaobo Li, Chen Ye, Hao Li, Haoyu Zhong, Yukai Shi, Zhijing Yang, Xiaojun Yang, Haoyu Zhong, Xin Li, Xin Jin, Yaojun Wu, Yingxue Pang, Sen Liu, Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li, Marie-Paule Cani, Wan-Chi Siu, Yuanbo Zhou, Rao Muhammad Umer, Christian Micheloni, Xiaofeng Cong, Rajat Gupta, Keon-Hee Ahn, Jun-Hyuk Kim, Jun-Ho Choi, Jong-Seok Lee, Feras Almasri, Thomas Vandamme, Olivier Debeir

* European Conference on Computer Vision Workshops, 2020 

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Component Divide-and-Conquer for Real-World Image Super-Resolution

Aug 05, 2020
Pengxu Wei, Ziwei Xie, Hannan Lu, Zongyuan Zhan, Qixiang Ye, Wangmeng Zuo, Liang Lin

* European Conference on Computer Vision (ECCV), 2020 

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Generalizing Energy-based Generative ConvNets from Particle Evolution Perspective

Oct 31, 2019
Yang Wu, Pengxu Wei, Xu Cai, Guanbin Li, Liang Lin

* To be appeared in T-PAMI 2020. We track and rederive the origin of the pGCN model from the perspective of particle evolution and discover the potential factors that may lead to a deteriorating quality of generated samples and instability of model training. The source code is publicly available at https://github.com/uiyo/GeneralizedGCN 

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Min-Entropy Latent Model for Weakly Supervised Object Detection

Feb 16, 2019
Fang Wan, Pengxu Wei, Zhenjun Han, Jianbin Jiao, Qixiang Ye

* Accepted by TPAMI 

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3D Human Pose Machines with Self-supervised Learning

Jan 15, 2019
Keze Wang, Liang Lin, Chenhan Jiang, Chen Qian, Pengxu Wei

* To appear in IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2019. Our simple yet effective self-supervised correction mechanism to incorporate 3D pose geometric structural information is innovative in the literature, and may also inspire other 3D vision tasks. Please find the code of this project at: http://www.sysu-hcp.net/3d_pose_ssl/ 

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