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

What is a subspace and what is not?

The de nition of a subspace is a subset Sof some Rn such that whenever u and v are vectors in S, so is u+ v for any two scalars (numbers) and . However, to identify and picture (geometrically) subspaces we use the following theorem: Theorem: A subset S of Rn is a subspace if and only if it is the span of a set of vectors, i.e.

  What, Subspaces, Is a subspace and what is not

4 Span and subspace - Auburn University

Subspace. A subset S of Rn is called a subspaceif the following hold: (a) 0∈ S, (b) x,y∈ S implies x+y∈ S, (c) x∈ S,α ∈ Rimplies αx∈ S. In other words, a subset S of Rn is a subspace if it satisfies the following: (a) S contains the origin 0, (b) S is closed under addition (meaning, if xand yare two vectors in S, then

  Span, Subspaces, 4 span and subspace

MATH 304 Linear Algebra Lecture 13: Span. Spanning set.

subspace of V if and only if S is nonempty and closed under linear operations, i.e., x,y ∈ S =⇒ x+y ∈ S, x ∈ S =⇒ rx ∈ S for all r ∈ R. Remarks. The zero vector in a subspace is the same as the zero vector in V. Also, the subtraction in a subspace agrees with that in V.

  Subspaces

Math 2331 { Linear Algebra

1 To show that H is a subspace of a vector space, use Theorem 1. 2 To show that a set is not a subspace of a vector space, provide a speci c example showing that at least one of the axioms a, b or c (from the de nition of a subspace) is violated. Jiwen He, University of Houston Math 2331, Linear Algebra 18 / 21

  Subspaces

Row Space, Column Space, and Nullspace

{ The row space of A is the subspace of <n spanned by the row vectors of A { The column space of A is the subspace of <m spanned by the column vectors of A. † Theorem: If a mxn matrix A is row-equivalent to a mxn matrix B, then the row space of A is equal to the row space of B. (NOT true for the column space)

  Space, Columns, Subspaces, Column space, And nullspace, Nullspace

Matrix Representations of Linear Transformations and ...

A subspace V of Rnis a subset of Rnthat contains the zero element and is closed under addition and scalar multiplication: (1) 0 2V (2) u;v 2V =)u+ v 2V (3) u 2V and k2R =)ku 2V Equivalently, V is a subspace if au+bv 2V for all a;b2R and u;v 2V. (You should try to prove that this is an equivalent statement to the rst.)

  Linear, Transformation, Matrix, Representation, Subspaces, Matrix representations of linear transformations and

Subspaces - Mathematics

The Subspace Test To test whether or not S is a subspace of some Vector Space Rn you must check two things: 1. if s 1 and s 2 are vectors in S, their sum must also be in S 2. if s is a vector in S and k is a scalar, ks must also be in S In other words, to test if a set is a subspace of a Vector Space, you only need to check if it closed under ...

  Subspaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces

Mathematics Course 111: Algebra I Part IV: Vector Spaces D. R. Wilkins Academic Year 1996-7 9 Vector Spaces A vector space over some field K is an algebraic structure consisting of a set V on which are defined