TransReID: Transformer-Based Object Re-Identification

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

The Basics of Structural Equation Modeling

Identification involves the study of conditions to obtain a single, unique solution for each and every free parameter specified in the model from the observed data. In order to obtain a solution, the number of free parameters, q, must be equal to or smaller than the

  Identification

ROTARY SCREW COMPRESSOR UNITS - Johnson Controls

MODELS 100 through 1080 RWF II Form 070.610-IOM (NOV 2014) ... discrepancy. Examine all items for damage in transit. ... Each compressor unit has 2 identification data plates. The compressor data plate containing compressor model and serial number is mounted on the compressor body. The

  Model, Identification, Control, Discrepancy, Johnson, Johnson controls

Twice Exceptional: Gifted Students with Learning ...

Identification Early identification of students who are gifted with LD is crucial (Dole, 2000). Many students who are gifted/LD are not identified until high school and college when academic work increases in difficulty. In earlier years, these students may appear to be functioning normally, but are usually performing well below their potential.

  Identification, Exceptional, Twice, Twice exceptional

Idaho Transportation Department

Vehicle Identification Number Inspection Certification Idaho Transportation Department ITD 3403 (Rev. 08-17) Supply # 019580380. Complete all sections related to Vehicle Do not use codes from any title Spell out makes and models This form must

  Department, Model, Identification, Inspection, Transportation, Idaho, Idaho transportation department

FMS-Standard description Version 04 13.10

- If there is a discrepancy between definitions in this document and the SAE, the SAE documents are valid only ... - The accuracy/interpretation of signals might differ depending on vehicle brand/models *. - (Bus) FMS-Standard is designed for Diesel engines. ... • added 2.2 Example SW Identification for buses and/or trucks • added Overview ...

  Model, Identification, Discrepancy

AAAI-21 Accepted Paper List.1.29

! 4!! 228:!Rain!Streak!Removal!via!Dual!Graph!Convolutional!Network! Xueyang!Fu,!Qi!Qi,!Yurui!Zhu,!Xinghao!Ding,!Zheng*Jun!Zha!! 233:!RevMan:!Revenue*Aware!Multi*Task ...

NEEDS ANALYSIS What Is Needs Analysis/Assessment? …

¾ Discrepancy identification, ordering differences between what ought to be and what is • Marketing Model ¾ This model defines needs assessment as a feedback process used by organizations to learn about and to adapt to the needs of their client populations. ¾ A marketing strategy of needs analysis has three components:

  Identification, Discrepancy, Discrepancy identification

Ethical Considerations for Working with Military Members ...

For an ethical–legal discrepancy to ... Examine several models for anticipating and responding to ... • Identification, Prevention, & Treatment of Suicidal Behavior in Service Members & Veterans (2.25 CE Credits) ...

  Model, Identification, Discrepancy

Cross-Modality Person Re-Identification via Modality ...

the modality discrepancy at the classifier level. [16] designs an auxiliary X-modality to mitigate the influence of modal-ity discrepancy. Generative adversarial networks have been adopted in cm-ReID, by generating data to mitigate the modality discrepancy. [37] generates cross-modality im-ages from two different modality images, and combines the

  Identification, Discrepancy