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”.
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
Advertisement
Documents from same domain
Image Style Transfer Using Convolutional Neural Networks
www.cv-foundation.orgImage Style Transfer Using Convolutional Neural Networks Leon A. Gatys Centre for Integrative Neuroscience, University of Tubingen, Germany¨ Bernstein Center for Computational Neuroscience, Tubingen, Germany¨
Single-Image Crowd Counting via Multi-Column …
www.cv-foundation.orgSingle-Image Crowd Counting via Multi-Column Convolutional Neural Network Yingying Zhang Desen Zhou Siqin Chen Shenghua Gao Yi Ma Shanghaitech University {zhangyy2,zhouds,chensq,gaoshh,mayi}@shanghaitech.edu.cn Abstract ... column CNN is adaptive to (hence the overall network
Convolutional Neural Networks at Constrained Time Cost
www.cv-foundation.orgConvolutional neural networks (CNNs) [15, 14] have re-cently brought in revolutions to the computer vision area. Deep CNNs not only have been continuously advancing the image classification accuracy [14, 21, 24, 1, 9, 22, 23], but also play as generic feature extractors for various recogni-tion tasks such as object detection [6, 9], semantic ...
Network, Neural, Convolutional, Constrained, Convolutional neural networks at constrained
Deep Convolutional Neural Fields for Depth Estimation From ...
www.cv-foundation.orgvolutional neural networks (CNN). CNN features have been setting new records for a wide variety of vision applica-tions [13]. Despite all the successes in classification prob-
Network, Neural network, Neural, Convolutional, Convolutional neural
Learning Spatiotemporal Features With 3D Convolutional ...
www.cv-foundation.orgthe networks lose their input’s temporal signal after the first convolution layer. Only the Slow Fusion model in [18] uses 3D convolutions and averaging pooling in its first 3convo-lution layers. We believe this is the key reason why it per-forms best …
Predicting the Future Behavior of a Time-Varying ...
www.cv-foundation.orgPredicting the Future Behavior of a Time-Varying Probability Distribution Christoph H. Lampert IST Austria chl@ist.ac.at Abstract We study the problem of predicting the future, though
Future, Time, Distribution, Probability, The future, Varying, A time varying probability distribution
Deep Residual Learning for Image Recognition
www.cv-foundation.orgthe residual learning principle is generic, and we expect that it is applicable in other vision and non-vision problems. 2. Related Work Residual Representations. In image recognition, VLAD [18] is a representation that encodes by the residual vectors with respect to a dictionary, and Fisher Vector [30] can be
Image, Learning, Residual, Recognition, Residual learning for image recognition, Image recognition, Residual learning
NTU RGB+D: A Large Scale Dataset for 3D Human Activity ...
www.cv-foundation.orgMultiview 3D event [43] and Northwestern-UCLA [40] datasets used more than one Kincect cameras at the same time to collect multi-view representations of the same ac-tion, and scale up the number of samples. It is worth mentioning, there are more than 40 datasets specifically for 3D human action recognition [47]. Al-
Unsupervised Visual Representation Learning by Context ...
www.cv-foundation.orghigh-resolution natural images. Unsupervisedrepresentation learning can also be formu-lated as learning an embedding (i.e. a feature vector for each image) where images that are semantically similar are close, while semantically different ones are far apart. One way to build such a representation is to create a supervised
High, Learning, Visual, Representation, Resolution, Unsupervised, Unsupervised visual representation learning by
Hierarchical Convolutional Features for Visual Tracking
www.cv-foundation.orgVisual representations are of great importance for object tracking. Numerous hand-crafted features have been used to represent the target appear-ance such as subspace representation [24] and color his-tograms [37]. The recent years have witnessed significant
Feature, Tracking, Visual, Representation, Hierarchical, Convolutional, Visual representation, Hierarchical convolutional features for visual tracking
Related documents
Building a Scalable and Secure Multi-VPC AWS Network ...
docs.aws.amazon.comBuilding 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
gee.cs.oswego.edu" 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
cs.stanford.edu(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.
The Bitcoin Lightning Network
lightning.networkThe 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
EfficientDet: Scalable and Efficient Object Detection
arxiv.orgEfficientDet: 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
metapath2vec: Scalable Representation Learning for ...
www3.nd.educonventional 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
EfficientDet: Scalable and Efficient Object Detection
openaccess.thecvf.comEfficientDet: Scalable and Efficient Object Detection Mingxing Tan Ruoming Pang Quoc V. Le Google Research, Brain Team {tanmingxing, rpang, qvl}@google.com Abstract Model efficiency has become increasingly important in computervision. In thispaper, we systematically study neu-ral network architecture design choices for object detec-
Intel Xeon Scalable Platform
www.intel.comThe 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
polkadot.networkKusama 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