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

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

What Have We Learned From Deep Representations for …

what these powerful models actually have learned. In this paper we shed light on deep spatiotemporal net-works by visualizing what excites the learned models us-ing activation maximization by backpropagating on the in-put. We are the first to visualize the hierarchical features

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

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

Facts for Teens: Conflict Resolution

With such approaches, conflict resolution education is interwoven with all classroom teaching, and teachers and staff are encouraged to promote effective conflict resolution principles and practices through their own behavior and through discipline and management practices.

  Approaches, Resolution

M -S C A D C - arXiv

scale contextual reasoning in combination with full-resolution output. Recent work has studied two approaches to dealing with the conflicting demands of multi-scale reasoning and full-resolution dense prediction. One approach involves repeated up …

  Approaches, Resolution

RICS Conflict avoidance and dispute resolution in construction

resolution, the applicable rules or strategies that might be adopted. However, Any surveyor adopting a good practice ... proactive conflict avoidance approaches such as the carrying out of a risk analysis; the production, updating and maintenance of a risk register as well

  Approaches, Resolution

Conflict Resolution Resource Guide - OACAS

Mar 31, 2017 · role diversity (e.g. race, gender, sexual orientation and identity) plays in conflict resolution, we included case studies that exemplify challenges related to diversity wherever possible. We also offer practical resources that address anti-oppressive approaches and practices when dealing

  Approaches, Resolution

Declaration on the Elimination of Violence against Women ...

Recalling also Economic and Social Council resolution 1991/18 of 30 May 1991, in which the Council ... ( f ) Develop, in a comprehensive way, preventive approaches and all those measures of …

  Approaches, Resolution

Participatory A Short Guide Asset Mapping to Community ...

several research approaches that are based on commu-nities collaborating with researchers (ex. Community Based Research), or community members engaging in ... resolution of community issues + There is value and legitimacy in the knowledge of individuals, families, and others in …

  Approaches, Resolution

Trauma-Informed Practices for Postsecondary Education: A …

Over the past 30 years, researchers have built a strong evidence base for trauma-informed approaches in medical and judicial fields . Awareness of trauma and its wide-reaching negative impacts is also becoming more widespread in education, and educators are developing their own approaches to help break the cycle of trauma for students .

  Trauma, Informed, Approaches, Trauma informed, Trauma informed approaches