Multi-Task Multi-Sensor Fusion for 3D Object Detection

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

Protocol for Use and Maintenance of Oxygen Monitoring …

when an oxygen monitoring device and/or new oxygen sensor is installed. 12-Month Interval Calibrations . These calibrations should be performed by the manufacturer or manufacturer’s representative either every 12 months or per the recommendation of the manufacturer, whichever is more frequent.

  Maintenance, Monitoring, Sensor, Oxygen, And maintenance of oxygen monitoring

General Purpose pH/ORP Sensors - Emerson Electric

A robust sensor design Extended sensor life and protection against poisoning ions using a double junction reference. Enhanced performance and increased life with cracking resistant glass. Maximum chemical resistance provided by a rugged polyphenylene sulfide body. Operates in sub-zero temperatures down to 14 °F (-10 °C).

  Design, Sensor, Sensor design

Daylight Sensor Design and Application Guide

Daylight Sensor | Design nd pplication uide An example of a Lutron daylighting system.* Partial open loop – Lutron approach In partial open loop daylighting, sensors are positioned inside the physical space and take into account the light levels penetrating the area from natural light sources, as well as light contributions from the work surface.

  Design, Sensor, Sensor design

MAESTRO LED+ DIMMER SENSOR SPEC (369748)

sensor dimmer should be mounted at least 4 ft (1.2 m) away from HVAC vents and light bulbs. • The performance of the sensor dimmer depends on a temperature differential between the ambient room temperature and that of room occupants. Warmer rooms may reduce the ability of the sensor dimmer to detect occupants. 35 ft (10.7 m)

  Sensor, Dimmers, Led dimmer sensor

Si7021-A20 I2C Humidity and Temperature Sensor

The Si7021 I2C Humidity and Temperature Sensor is a monolithic CMOS IC integrating humidity and temperature sensor elements, an analog-to-digital converter, signal processing, calibration data, and an I2C Interface. The patented use of industry-standard, low-K polymeric dielectrics for sensing humidity enables

  Sensor

Typical Application - SparkFun Electronics

the conductive path are electrically isolated from the sensor leads (pins 5 through 8). This allows the ACS712 current sensor to be used in applications requiring electrical isolation without the use of opto-isolators or other costly isolation techniques. The ACS712 is provided in a small, surface mount SOIC8 package.

  Applications, Electronic, Sensor, Sparkfun, Sparkfun electronics

STM32L1X temperature sensor example STMicroelectronics ...

The sensor provides good linearity but quite poor interchangeability and must be calibrated to obtain good overall accuracy. If the application is designed to only measure the relative temperature variations, the temperature sensor does not need to be calibrated. 1.2 Temperature measurement and data processing

  Sensor