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

Mother-Tongue Interference in the Acquisition of English ...

Contrastive analysis is concerned with the study of a pair of languages with the aim of discovering their structural similarities and differences. Contrastive Analysis is a method that was widely used in the 1960s and early 1970s to explain why some features of a target language were more difficult to learn than others. (Mozlan, 2015)

  Analysis, Contrastive, Contrastive analysis

AN ANALYSIS OF SYNTACTIC ERRORS COMMITTED BY …

His study was based on contrastive analysis of English and Arabic. He devised a test focusing on the problem areas and sorted out the frequency and types of the structural errors which were mostly related to tense. Kambal (1980) studied the written errors of the Khartoum university students in Sudan and found that their errors fell in the areas ...

  Analysis, Contrastive, Contrastive analysis

. An Analysis of Language Teaching Approaches and Methods ...

Audiolingualism reflects the descriptive, structural, and contrastive linguistics of the fifties and sixties. Its psychological basis is behaviorism which interprets language learning in terms of stimulus and response, operant conditioning, and reinforcement with an emphasis on successful error-free learning. It assumes that learning a

  Analysis, Contrastive

Learning Implicit Sentiment in Aspect-based Sentiment ...

Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training Zhengyan Li 1, Yicheng Zou , Chong Zhang , Qi Zhang and Zhongyu Wei2 1Shanghai Key Laboratory of Intelligent Information Processing, School of Computer Science, Fudan University, Shanghai, China 2School of Data Science, Fudan University

  Analysis, Contrastive

arXiv:2006.13979v2 [cs.CL] 15 Dec 2020

Analysis shows that the latent discrete speech representations are shared across languages with increased shar- ... The model is trained by solving a contrastive task over masked feature encoder outputs. For masking, we sample p= 0:065 of all time steps to be starting indices and mask the subsequent M= 10 time 2.

  Analysis, Contrastive

Abstract arXiv:2012.09740v1 [cs.LG] 15 Dec 2020

•With a gradient analysis, we show that the temperature is a key parameter to control the strength of penalties on hard negative samples. •We show that there exists a uniformity-tolerance dilemma in contrastive learning, a good choice of tem-perature can compromise the two properties and im-prove the feature quality remarkably.

  Analysis, Contrastive

Contrastive Analysis, Error Analysis, Interlanguage 1

Contrastive analysis became associated with behaviorist psychology, which was another separate influence on language teaching, particularly on audiolingual language teaching, and especially in the United States. Behaviorism was a general theory of learning. It viewed learning as habit formation brought about

  Analysis, Errors, Error analysis, Contrastive, Interlanguage, Contrastive analysis

Sentiment Analysis and Opinion Mining

subjectivity analysis, affect analysis, emotion analysis, review mining, etc. However, they are now all under the umbrella of sentiment analysis or opinion mining. While in industry, the term sentiment analysis is more commonly used, but in academia both sentiment analysis and opinion mining are frequently employed.

  Analysis, Sentiment, Sentiment analysis

Paper #1: Comparative Analysis - Kansas State University

Paper #1: Comparative Analysis Basic Assignment. Choose two of the first four texts on our semester's schedule and write a four-to-six page paper that compares the two works of fiction. Examples and Advice. You might compare the two realists (or the two sentimentalists) who take different approaches within the same genre.

  States, Analysis, Kansas, University, Kansas state university