Y
Yuzhong Liu
Researcher at National University of Defense Technology
Publications - 3
Citations - 64
Yuzhong Liu is an academic researcher from National University of Defense Technology. The author has contributed to research in topics: Standard illuminant & Orientation (computer vision). The author has an hindex of 2, co-authored 3 publications receiving 52 citations.
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Book ChapterDOI
AIM 2020: Scene Relighting and Illumination Estimation Challenge
Majed El Helou,Ruofan Zhou,Sabine Süsstrunk,Radu Timofte,Mahmoud Afifi,Michael S. Brown,Kele Xu,Hengxing Cai,Yuzhong Liu,Li-Wen Wang,Zhi-Song Liu,Chu-Tak Li,Sourya Dipta Das,Nisarg Shah,Akashdeep Jassal,Tongtong Zhao,Shanshan Zhao,Sabari Nathan,M. Parisa Beham,R. Suganya,Qing Wang,Zhongyun Hu,Xin Huang,Yaning Li,Maitreya Suin,Kuldeep Purohit,A. N. Rajagopalan,Densen Puthussery,P. S. Hrishikesh,Melvin Kuriakose,C. V. Jiji,Yu Zhu,Liping Dong,Zhuolong Jiang,Chenghua Li,Cong Leng,Jian Cheng +36 more
TL;DR: The AIM 2020 challenge on virtual image relighting and illumination estimation as discussed by the authors focused on one-to-one relighting, where the objective was to relight an input photo of a scene with a different color temperature and illuminant orientation.
Posted Content
AIM 2020: Scene Relighting and Illumination Estimation Challenge
Majed El Helou,Ruofan Zhou,Sabine Süsstrunk,Radu Timofte,Mahmoud Afifi,Michael S. Brown,Kele Xu,Hengxing Cai,Yuzhong Liu,Li-Wen Wang,Zhi-Song Liu,Chu-Tak Li,Sourya Dipta Das,Nisarg Shah,Akashdeep Jassal,Tongtong Zhao,Shanshan Zhao,Sabari Nathan,M. Parisa Beham,R. Suganya,Qing Wang,Zhongyun Hu,Xin Huang,Yaning Li,Maitreya Suin,Kuldeep Purohit,A. N. Rajagopalan,Densen Puthussery,Hrishikesh P S,Melvin Kuriakose,C. V. Jiji,Yu Zhu,Liping Dong,Zhuolong Jiang,Chenghua Li,Cong Leng,Jian Cheng +36 more
TL;DR: The novel VIDIT dataset used in the AIM 2020 challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks are presented.
Proceedings ArticleDOI
Multi-Scale Generalized Attention-Based Regional Maximum Activation of Convolutions for Beauty Product Retrieval
TL;DR: This paper proposes a novel descriptors, named Multi-Scale Generalized Attention-Based Regional Maximum Activation of Convolutions (MS-GRMAC), which introduces multi-scale generalized attention mechanism to reduce the influence of scale variations, thus, can boost the performance of the retrieval task.