Finding Tiny Faces in the Wild With Generative Adversarial ...

faces, which are unfriendly for the face classifier. Toward-s this end, we design a refinement sub-network to recover some detailed information. In the discriminator network, the basic GAN [17, 12, 8] is trained to distinguish the real and fake high resolution images. To classify faces or non-

  Faces

Squeeze-and-Excitation Networks - openaccess.thecvf.com

Squeeze-and-Excitation Networks Jie Hu1∗ Li Shen2∗ Gang Sun1 hujie@momenta.ai lishen@robots.ox.ac.uk sungang@momenta.ai 1 Momenta 2 Department of Engineering Science, University of Oxford Abstract Convolutional neural networks are built upon the con-

  Network, Excitation, Squeeze and excitation networks, Squeeze

RegularFace: Deep Face Recognition via Exclusive ...

RegularFace: Deep Face Recognition via Exclusive Regularization Kai Zhao Jingyi Xu Ming-Ming Cheng ∗ TKLNDST, CS, Nankai University kaiz.xyz@gmail.com cmm@nankai.edu.cn

  Zhao

Protecting World Leaders Against Deep Fakes

Protecting World Leaders Against Deep Fakes Shruti Agarwal and Hany Farid University of California, Berkeley Berkeley CA, USA {shrutiagarwal, hfarid}@berkeley.edu

Auto-DeepLab: Hierarchical Neural Architecture Search for ...

Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation Chenxi Liu1∗, Liang-Chieh Chen 2, Florian Schroff2, Hartwig Adam2, Wei Hua2, Alan Yuille1, Li Fei-Fei3 1Johns Hopkins University 2Google 3Stanford University Abstract Recently, NeuralArchitectureSearch(NAS)hassuccess-

PointNet: Deep Learning on Point Sets ... - CVF Open Access

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Charles R. Qi* Hao Su* Kaichun Mo Leonidas J. Guibas Stanford University

  Open, Learning, Points, Deep, Sets, Pointnet, Deep learning on point sets

Frustum PointNets for 3D Object Detection From RGB-D Data

Frustum PointNets for 3D Object Detection from RGB-D Data Charles R. Qi1∗ Wei Liu2 Chenxia Wu2 Hao Su3 Leonidas J. Guibas1 1Stanford University 2Nuro, Inc. 3UC San Diego Abstract In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.

Class-Balanced Loss Based on Effective Number of Samples

and large-scale datasets including ImageNet and iNatural-ist. Our results show that when trained with the proposed class-balanced loss, the network is able to achieve signifi-cant performance gains on long-tailed datasets. 1. Introduction The recent success of deep Convolutional Neural Net-works (CNNs) for visual recognition [26, 37, 38, 16] owes

  Scale, Visual, Recognition, Visual recognition

ESRGAN: Enhanced Super-Resolution Generative Adversarial ...

ESRGAN: EnhancedSuper-Resolution Generative Adversarial Networks Xintao Wang 1, Ke Yu , Shixiang Wu2, Jinjin Gu3, Yihao Liu4, Chao Dong 2, Yu Qiao , and Chen Change Loy5 1 CUHK-SenseTime Joint Lab, The Chinese University of Hong Kong 2 Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences 3 The Chinese University of Hong Kong, …

  Network, Adversarial, Generative, Generative adversarial, Generative adversarial networks

CartoonGAN: Generative Adversarial Networks for Photo ...

is to use Generative Adversarial Networks (GANs) [9, 34], which produce state-of-the-art results in many applications suchastexttoimagetranslation[24],imageinpainting[37], image super-resolution [19], etc. The key idea of a GAN model is to train two networks (i.e., a generator and a dis-criminator) iteratively, whereby the adversarial loss pro-

  Network, Adversarial, Generative, Generative adversarial networks

Recent Emerging Market Crises: What Have We Learned?

Recent Emerging Market Crises: What Have We Learned? Guillermo Ortiz* It is an honor to be invited to deliver this lecture in memory of Per Jacobsson, a man who dedicated his life with great suc-

  What, Center, Have, Market, Emerging, Crises, Learned, What we have learned, Recent emerging market crises

PRP update: What have we learned? - AAOM

What have we learned? Dr José Fábio Lana . Summary •PRP – definition and controversies •Collecting and obtaining different types •PRP contents •How we do it? •Proposal of a new classification : MARSPILL . Autologous non-immunogenic therapy PRP Contains a high concentration of growth factors

  What, Have, Learned, What we have learned

Nutritional Deficiencies following Bariatric Surgery: What ...

Nutritional Deficiencies following Bariatric Surgery: What Have We Learned? Richard D. Bloomberg, MD, FRCSC; Amy Fleishman, MS, RD, CDN; ... Nutritional Deficiencies following Bariatric Surgery Obesity Surgery, 15, 2005 147 Table 2. Studies of protein deficiency ... others have not observed this trend. In a small-sample study by

  What, Have, Following, Deficiencies, Surgery, Nutritional, Learned, Bariatric, What we have learned, Nutritional deficiencies following bariatric surgery

OPTIMIZING DIFFERENT HAY TYPES FOR HORSES: WHAT …

OPTIMIZING DIFFERENT HAY TYPES FOR HORSES: WHAT HAVE WE LEARNED? Anne Rodiek1 ABSTRACT Good quality hay is the cornerstone of all horse feeding programs. Healthy adult horses can do well on diets composed entirely of good quality hay, either grass or legume. Growing horses and

  What, Types, Optimizing, Have, Different, Learned, What we have learned, Optimizing different hay types for

Cybersecurity: What Have We Learned? - nsci-va.org

information, we hope to provide periodic updates to these lessons learned as technologies and threats continue to evolve – something they seem to be doing at a stunning pace. The most famous example of

  What, Have, Cybersecurity, Learned, What we have learned

Academic research on FIN 48: What have we learned?

2 which led to its issuance. There are several important caveats to the literature review. The first caveat is that there are only four papers published in academic journals that study the impact of

  Research, What, Academic, Have, Learned, What we have learned, Academic research on fin 48

Review Hematopoietic stem cell transplantation for ...

Review Hematopoietic stem cell transplantation for autoimmune diseases: What have we learned? Richard K. Burt a,*, Alessandro Testor a, Robert Craig b, Bruce Cohen c, Robert Suffit c, Walter Barr d a Division of Immunotherapy, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA b Division of Gastroenterology, Department of Medicine, …

  What, Review, Disease, Have, Learned, Cells, Stem, Autoimmune, Transplantation, Hematopoietic, What we have learned, Review hematopoietic stem cell transplantation, Review hematopoietic stem cell transplantation for autoimmune diseases

What Have We Learned from the PDP-1 I? - Gordon Bell

What Have We Learned from the PDP-ll? 9 the same lines, but more direct: beginning with the applied technology manufacturers, material moves through computer manufacturing and then

  Form, What, Have, Learned, What have we learned from the

What have we learned about the causes of corruption from ...

What have we learned about the causes of corruption from ten years of crossnational empirical research? I review recent efforts by political scientists and economists to explain

  Research, What, Year, Have, Learned, Empirical, What we have learned, Ten years of crossnational empirical research, Crossnational

Designing Subsidized Rental Housing Programs: What Have …

We describe the circumstances in which there is a case for providing project-based assistance as a supplement to tenant-based housing vouchers and the policy goals that such a policy should pursue.

  What, Have, What have