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

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

Maps and Map Learning in Social Studies

fied reading, interpreting, and analyzing maps. They expected their students to evaluate the information provided by the maps, to make inferences and deci-sions based on that information, to gain what one teacher called an “appreciation of spatial perspectives and understand-

  Amps, Analyzing, Analyzing maps

Analyzing Character Traits - Weebly

In addition, all of the character maps are available in landscape format in a separate PDF file for use with an interactive whiteboard. These lessons are designed to take place intermittently over a period of several weeks or ... If you enjoyed my Analyzing Character Traits pack, please

  Character, Amps, Traits, Analyzing, Analyzing character traits, Character maps

NYS K-8 Social Studies Framework - New York State ...

histories, maps, and graphs). Recognize, use, and analyze different forms of evidence to make meaning in social studies (including primary and secondary sources, such as art and photographs, artifacts, oral histories, maps, and graphs). Identify the author or creator of a book or map. Identify the creator and/or author of different forms of ...

  Social, Studies, Social studies, Amps

Performance Management Plan Toolkit - USAID Learning Lab

Reviewing and analyzing performance data to monitor progress toward achieving results in the R/CDCS and Project LogFrames Planning and budgeting for evaluations Managing, analyzing, communicating and reporting performance data, and Using …

  Performance, Analyzing, Analyzing performance

Transformative Learning: Theory to Practice

the Australian government, employers, and academics include analyzing infor-mation, communicating ideas, planning and organizing activities, using math-ematical ideas and technology, working in teams, solving problems, and using cultural understandings (Gonzi and others, 1995). The common presumption in these lists is that the essential learning

  Learning, Analyzing, Transformative, Transformative learning

What Process Do Historians Use to Investigate the Past?

What Process Do Historians Use to Investigate the Past? Unit 1 - Lesson 5 Content Expectations 6 and 7 Explain how historians use a variety of sources to explore the past (e.g., H1.2.1: artifacts, primary and secondary sources including narratives, technology, historical maps, visual/mathematical quantitative data, radiocarbon dating, DNA

  Amps, Historian

THE APUSH Short answer question (SAQ)

• Argumentation (identifying and analyzing argument, bias) • Causation (cause/effect) • Comparison (similarities and differences) The response to each question is no more than three to four sentences (hence, the SHORT description). This …

  Analyzing

Understanding Text Structure

4. Give students an understanding of plot. Make sure to encourage students to look for the information included in the introduction or exposition of a …

  Texts, Structure, Text structure

READING LITERARY (RL) READING ... - Georgia Standards

Mar 02, 2015 · Determine the meaning of words and phrases as they are used in a text, including figurative and connotative meanings; analyze the impact of specific word choices on meaning and tone, including analogies or allusions to

  Standards, Georgia, Georgia standards