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

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

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

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

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.

Building a Scalable and Secure Multi-VPC AWS Network ...

Building a Scalable and Secure Multi-VPC AWS Network Infrastructure AWS Whitepaper Abstract Building a Scalable and Secure Multi-VPC AWS Network Infrastructure Publication date: June 10, 2020 (Document History (p. 29)) Abstract AWS customers often rely on hundreds of accounts and VPCs to segment their workloads and expand their footprint.

  Multi, Whitepaper, Network, Infrastructures, Scalable, Multi vpc aws network infrastructure aws whitepaper, Multi vpc aws network infrastructure

Scalable IO in Java http://gee.cs.oswego

" Scalable network services " Event-driven processing " Reactor pattern Basic version Multithreaded versions Other variants ... " Can extend basic network service patterns Handle many relatively long-lived clients Track client and session state (including drops) Distribute services across multiple hosts.

  Network, Java, Scalable, Scalable network, Scalable io in java

node2vec: Scalable Feature Learning for Networks

(sample) network neighborhoods for nodes. Our key contribution is in defining a flexible notion of a node’s network neighborhood. By choosing an appropriate notion of a neighborhood, node2vec can learn representations that organize nodes based on their network roles and/or communities they be-long to.

  Network, Scalable, Node2vec

The Bitcoin Lightning Network

The Bitcoin Lightning Network: Scalable O -Chain Instant Payments Joseph Poon joseph@lightning.network Thaddeus Dryja rx@awsomnet.org January 14, 2016 DRAFT Version 0.5.9.2 Abstract The bitcoin protocol can encompass the global nancial transac-tion volume in all electronic payment systems today, without a single

  Network, Lightning, Scalable, Lightning network

EfficientDet: Scalable and Efficient Object Detection

EfficientDet: Scalable and Efficient Object Detection Mingxing Tan Ruoming Pang Quoc V. Le Google Research, Brain Team ftanmingxing, rpang, qvlg@google.com Abstract Model efficiency has become increasingly important in computer vision. In this paper, we systematically study neu-ral network architecture design choices for object detection

  Network, Scalable

metapath2vec: Scalable Representation Learning for ...

conventional network embedding techniques. We develop two scalable representation learning models, namely metapath2vec and metapath2vec++. „e metapath2vec model formalizes meta-path-based random walks to construct the heterogeneous neighborhood of a node and then leverages a heterogeneous skip-gram model

  Network, Scalable

Intel Xeon Scalable Platform

The Intel® Xeon® Scalable platform provides the foundation for a powerful data center platform that creates an evolutionary leap in agility and scalability.3 Disruptive by design, this innovative processor sets a new level of platform convergence and capabilities across compute, storage, memory, network, and security.

  Intel, Xeon, Network, Platform, Scalable, Intel xeon scalable platform, 174 scalable platform

An Introduction to Polkadot

Kusama Network 12 Kusama is an early, unaudited and unrefined release of Polkadot created to test the network’s technology and economic incentives in a real-world environment. It’s also the perfect place for parachain developers to test ideas before deploying to Polkadot. Kusama is owned and governed by a community of supporters who hold KSM

  Network, Polkadot

Scalable Person Re-Identification: A Benchmark

Scalable Person Re-identification: A Benchmark Liang Zheng†‡∗, Liyue Shen†∗, Lu Tian†∗, Shengjin Wang†, Jingdong Wang§, Qi Tian‡ †Tsinghua University §Microsoft Research ‡University of Texas at San Antonio Abstract This paper contributes a new high quality dataset for person re-identification, named “Market-1501”.

  Scalable