Example: confidence
and Super-Resolution arXiv:1603.08155v1 [cs.CV] 27 Mar 2016
Perceptual Losses for Real-Time Style Transfer and Super-Resolution 5 To address the shortcomings of per-pixel losses and allow our loss functions to better measure perceptual and semantic di erences between images, we draw inspiration from recent work that generates images via optimization [6,7,8,9,10].
Tags:
Information
Domain:
Source:
Link to this page:
Documents from same domain
![arXiv:0706.3639v1 [cs.AI] 25 Jun 2007](/cache/preview/4/1/3/9/3/1/4/b/thumb-4139314b93ef86b7b4c2d05ebcc88e46.jpg)
arXiv:0706.3639v1 [cs.AI] 25 Jun 2007
arxiv.orgarXiv:0706.3639v1 [cs.AI] 25 Jun 2007 Technical Report IDSIA-07-07 A Collection of Definitions of Intelligence Shane Legg IDSIA, Galleria …
Deep Residual Learning for Image Recognition - …
arxiv.orgDeep Residual Learning for Image Recognition Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun Microsoft Research fkahe, v-xiangz, v-shren, jiansung@microsoft.com
![arXiv:1301.3781v3 [cs.CL] 7 Sep 2013](/cache/preview/4/d/5/0/4/3/4/0/thumb-4d504340120163c0bdf3f4678d8d217f.jpg)
arXiv:1301.3781v3 [cs.CL] 7 Sep 2013
arxiv.orgFor all the following models, the training complexity is proportional to O = E T Q; (1) where E is number of the training epochs, T is the number of …
![@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016](/cache/preview/c/3/4/9/4/6/9/b/thumb-c349469b499107d21e221f2ac908f8b2.jpg)
@google.com arXiv:1609.03499v2 [cs.SD] 19 Sep 2016
arxiv.orgwhere 1 <x t <1 and = 255. This non-linear quantization produces a significantly better reconstruction than a simple linear quantization scheme. …
A Tutorial on UAVs for Wireless Networks: …
arxiv.orgA Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems Mohammad Mozaffari 1, ... to UAVs in wireless communications is the work in …
Adversarial Generative Nets: Neural Network …
arxiv.orgAdversarial Generative Nets: Neural Network Attacks on State-of-the-Art Face Recognition Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer Carnegie Mellon University
Massive Exploration of Neural Machine Translation ...
arxiv.orgMassive Exploration of Neural Machine Translation Architectures Denny Britzy, Anna Goldie, Minh-Thang Luong, Quoc Le fdennybritz,agoldie,thangluong,qvlg@google.com Google Brain
Mastering Chess and Shogi by Self-Play with a …
arxiv.orgMastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm David Silver, 1Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, 1Matthew Lai, Arthur Guez, Marc Lanctot,1
Going deeper with convolutions - arXiv
arxiv.orgGoing deeper with convolutions Christian Szegedy Google Inc. Wei Liu University of North Carolina, Chapel Hill Yangqing Jia Google Inc. Pierre Sermanet
Andrew G. Howard Menglong Zhu Bo Chen Dmitry ...
arxiv.orgMobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand Marco Andreetto Hartwig Adam
Related documents
ESRGAN: Enhanced Super-Resolution Generative Adversarial ...
openaccess.thecvf.comperceptual-quality aware manner based on [6]. The perceptual quality is judged by the non-reference measures of Ma’s score [27] and NIQE [30], i.e., perceptual index = 1 2((10 − Ma) + NIQE). A lower perceptual index represents a better perceptual quality. As shown in Fig. 2, the perception-distortion plane is divided into three
Perceptual Generative Adversarial Networks for Small ...
openaccess.thecvf.comPerceptual Generative Adversarial Networks for Small Object Detection Jianan Li1 Xiaodan Liang2 Yunchao Wei3 Tingfa Xu1∗ Jiashi Feng 3 Shuicheng Yan3,4 1 Beijing Institute of Technology 2 CMU 3 National University of Singapore 4 360 AI Institute {20090964, ciom xtf1}@bit.edu.cn xiaodan1@cs.cmu.edu {eleweiyv, elefjia}@nus.edu.sg yanshuicheng@360.cn