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pro vyhledávání: '"Huang, Thomas S."'
Autor:
Li, Jiachen, Cheng, Bowen, Feris, Rogerio, Xiong, Jinjun, Huang, Thomas S., Hwu, Wen-Mei, Shi, Humphrey
Current anchor-free object detectors are quite simple and effective yet lack accurate label assignment methods, which limits their potential in competing with classic anchor-based models that are supported by well-designed assignment methods based on
Externí odkaz:
http://arxiv.org/abs/2104.14082
Video instance segmentation is a complex task in which we need to detect, segment, and track each object for any given video. Previous approaches only utilize single-frame features for the detection, segmentation, and tracking of objects and they suf
Externí odkaz:
http://arxiv.org/abs/2012.03400
Cardiac motion estimation plays a key role in MRI cardiac feature tracking and function assessment such as myocardium strain. In this paper, we propose Motion Pyramid Networks, a novel deep learning-based approach for accurate and efficient cardiac m
Externí odkaz:
http://arxiv.org/abs/2006.15710
Inspired by the robustness and efficiency of sparse representation in sparse coding based image restoration models, we investigate the sparsity of neurons in deep networks. Our method structurally enforces sparsity constraints upon hidden neurons. Th
Externí odkaz:
http://arxiv.org/abs/2006.04357
Deep convolution-based single image super-resolution (SISR) networks embrace the benefits of learning from large-scale external image resources for local recovery, yet most existing works have ignored the long-range feature-wise similarities in natur
Externí odkaz:
http://arxiv.org/abs/2006.01424
Autor:
Zhang, Kai, Gu, Shuhang, Timofte, Radu, Shang, Taizhang, Dai, Qiuju, Zhu, Shengchen, Yang, Tong, Guo, Yandong, Jo, Younghyun, Yang, Sejong, Kim, Seon Joo, Zha, Lin, Jiang, Jiande, Gao, Xinbo, Lu, Wen, Liu, Jing, Yoon, Kwangjin, Jeon, Taegyun, Akita, Kazutoshi, Ooba, Takeru, Ukita, Norimichi, Luo, Zhipeng, Yao, Yuehan, Xu, Zhenyu, He, Dongliang, Wu, Wenhao, Ding, Yukang, Li, Chao, Li, Fu, Wen, Shilei, Li, Jianwei, Yang, Fuzhi, Yang, Huan, Fu, Jianlong, Kim, Byung-Hoon, Baek, JaeHyun, Ye, Jong Chul, Fan, Yuchen, Huang, Thomas S., Lee, Junyeop, Lee, Bokyeung, Min, Jungki, Kim, Gwantae, Lee, Kanghyu, Park, Jaihyun, Mykhailych, Mykola, Zhong, Haoyu, Shi, Yukai, Yang, Xiaojun, Yang, Zhijing, Lin, Liang, Zhao, Tongtong, Peng, Jinjia, Wang, Huibing, Jin, Zhi, Wu, Jiahao, Chen, Yifu, Shang, Chenming, Zhang, Huanrong, Min, Jeongki, S, Hrishikesh P, Puthussery, Densen, C V, Jiji
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor 16 based on a set of prior examples of
Externí odkaz:
http://arxiv.org/abs/2005.01056