咨询与建议

限定检索结果

文献类型

  • 1,535 篇 会议
  • 21 册 图书
  • 13 篇 期刊文献

馆藏范围

  • 1,569 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 1,449 篇 工学
    • 1,046 篇 计算机科学与技术...
    • 655 篇 机械工程
    • 358 篇 电气工程
    • 111 篇 软件工程
    • 55 篇 控制科学与工程
    • 49 篇 信息与通信工程
    • 35 篇 光学工程
    • 28 篇 仪器科学与技术
    • 17 篇 网络空间安全
    • 15 篇 生物工程
    • 9 篇 生物医学工程(可授...
    • 8 篇 电子科学与技术(可...
    • 8 篇 安全科学与工程
    • 7 篇 测绘科学与技术
    • 4 篇 化学工程与技术
    • 3 篇 建筑学
  • 112 篇 医学
    • 108 篇 临床医学
    • 6 篇 基础医学(可授医学...
    • 4 篇 特种医学
  • 87 篇 理学
    • 38 篇 物理学
    • 34 篇 数学
    • 24 篇 生物学
    • 12 篇 统计学(可授理学、...
    • 9 篇 系统科学
    • 5 篇 化学
  • 42 篇 管理学
    • 32 篇 图书情报与档案管...
    • 10 篇 管理科学与工程(可...
  • 24 篇 艺术学
    • 24 篇 设计学(可授艺术学...
  • 19 篇 法学
    • 19 篇 社会学
  • 15 篇 文学
    • 15 篇 新闻传播学
  • 2 篇 教育学
  • 2 篇 农学
  • 1 篇 经济学

主题

  • 528 篇 computer vision
  • 139 篇 face recognition
  • 135 篇 pattern recognit...
  • 135 篇 feature extracti...
  • 130 篇 cameras
  • 129 篇 image segmentati...
  • 128 篇 object recogniti...
  • 115 篇 object detection
  • 103 篇 training
  • 98 篇 robustness
  • 94 篇 images
  • 92 篇 image recognitio...
  • 90 篇 shape
  • 90 篇 layout
  • 84 篇 visualization
  • 77 篇 image reconstruc...
  • 76 篇 humans
  • 70 篇 computer science
  • 66 篇 computational mo...
  • 66 篇 image classifica...

机构

  • 23 篇 rhein westfal th...
  • 18 篇 carnegie mellon ...
  • 16 篇 chinese acad sci...
  • 15 篇 stanford univ st...
  • 14 篇 univ chinese aca...
  • 11 篇 australian natl ...
  • 11 篇 univ calif berke...
  • 10 篇 univ sci & techn...
  • 10 篇 mit cambridge ma...
  • 10 篇 univ maryland co...
  • 9 篇 microsoft res as...
  • 9 篇 univ washington ...
  • 8 篇 microsoft resear...
  • 8 篇 microsoft res re...
  • 8 篇 natl univ singap...
  • 7 篇 chinese univ hon...
  • 7 篇 tech univ munich...
  • 6 篇 mpi intelligent ...
  • 6 篇 kaust thuwal
  • 6 篇 imperial coll lo...

作者

  • 20 篇 leibe bastian
  • 12 篇 ji qiang
  • 10 篇 li stan z.
  • 9 篇 pal umapada
  • 8 篇 zhang lei
  • 8 篇 chellappa rama
  • 8 篇 lei zhen
  • 8 篇 zafeiriou stefan...
  • 8 篇 hu weiming
  • 8 篇 hua gang
  • 7 篇 ramanan deva
  • 7 篇 wang xiaogang
  • 7 篇 yan shuicheng
  • 7 篇 mubarak shah
  • 6 篇 van gool luc
  • 6 篇 darrell trevor
  • 6 篇 luiten jonathon
  • 6 篇 pollefeys marc
  • 6 篇 bischof horst
  • 6 篇 ghanem bernard

语言

  • 1,554 篇 英文
  • 9 篇 土耳其文
  • 2 篇 日文
  • 2 篇 其他
  • 1 篇 西班牙文
  • 1 篇 中文
检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR"
1569 条 记 录,以下是71-80 订阅
排序:
Bilinear Programming for Human Activity recognition with Unknown MRF Graphs
Bilinear Programming for Human Activity Recognition with Unk...
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Wang, Zhenhua Shi, Qinfeng Shen, Chunhua van den Hengel, Anton Univ Adelaide Sch Comp Sci Adelaide SA 5005 Australia
Markov Random Fields (MRFs) have been successfully applied to human activity modelling, largely due to their ability to model complex dependencies and deal with local uncertainty. However, the underlying graph structu... 详细信息
来源: 评论
Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots
Watching Unlabeled Video Helps Learn New Human Actions from ...
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Chen, Chao-Yeh Grauman, Kristen Univ Texas Austin Austin TX 78712 USA
We propose an approach to learn action categories from static images that leverages prior observations of generic human motion to augment its training process. Using unlabeled video containing various human activities... 详细信息
来源: 评论
Poselet Key-framing: A Model for Human Activity recognition
Poselet Key-framing: A Model for Human Activity Recognition
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Raptis, Michalis Sigal, Leonid Disney Res Pittsburgh PA 15213 USA
In this paper, we develop a new model for recognizing human actions. An action is modeled as a very sparse sequence of temporally local discriminative keyframes - collections of partial key-poses of the actor(s), depi... 详细信息
来源: 评论
Kernel Learning for Extrinsic Classification of Manifold Features
Kernel Learning for Extrinsic Classification of Manifold Fea...
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Vemulapalli, Raviteja Pillai, Jaishanker K. Chellappa, Rama Univ Maryland Dept Elect & Comp Engn Ctr Automat Res UMIACS College Pk MD 20742 USA
In computer vision applications, features often lie on Riemannian manifolds with known geometry. Popular learning algorithms such as discriminant analysis, partial least squares, support vector machines, etc., are not... 详细信息
来源: 评论
Enriching Texture Analysis with Semantic Data
Enriching Texture Analysis with Semantic Data
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Matthews, Tim Nixon, Mark S. Niranjan, Mahesan Univ Southampton Sch Elect & Comp Sci Commun Signal Proc & Control Grp Southampton SO9 5NH Hants England
We argue for the importance of explicit semantic modelling in human-centred texture analysis tasks such as retrieval, annotation, synthesis, and zero-shot learning. To this end, low-level attributes are selected and u... 详细信息
来源: 评论
Ensemble Learning for Confidence Measures in Stereo vision
Ensemble Learning for Confidence Measures in Stereo Vision
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Haeusler, Ralf Nair, Rahul Kondermann, Daniel Univ Auckland Dept Comp Sci Auckland 1 New Zealand Heidelberg Univ Heidelberg Collaboratory Image Proc D-69115 Heidelberg Germany
With the aim to improve accuracy of stereo confidence measures, we apply the random decision forest framework to a large set of diverse stereo confidence measures. Learning and testing sets were drawn from the recentl... 详细信息
来源: 评论
Facial Feature Tracking under Varying Facial Expressions and Face Poses based on Restricted Boltzmann Machines
Facial Feature Tracking under Varying Facial Expressions and...
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Wu, Yue Wang, Zuoguan Ji, Qiang Rensselaer Polytech Inst ECSE Dept Troy NY 12181 USA
Facial feature tracking is an active area in computer vision due to its relevance to many applications. It is a non-trivial task, since faces may have varying facial expressions, poses or occlusions. In this paper, we... 详细信息
来源: 评论
Graph Matching with Anchor Nodes: A Learning Approach
Graph Matching with Anchor Nodes: A Learning Approach
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Hu, Nan Rustamov, Raif M. Guibas, Leonidas Stanford Univ Stanford CA 94305 USA
In this paper, we consider the weighted graph matching problem with partially disclosed correspondences between a number of anchor nodes. Our construction exploits recently introduced node signatures based on graph La... 详细信息
来源: 评论
Intrinsic Scene Properties from a Single RGB-D Image
Intrinsic Scene Properties from a Single RGB-D Image
收藏 引用
26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Barron, Jonathan T. Malik, Jitendra Univ Calif Berkeley Berkeley CA 94720 USA
In this paper we extend the "shape, illumination and reflectance from shading" (SIRFS) model [3, 4], which recovers intrinsic scene properties from a single image. though SIRFS performs well on images of seg... 详细信息
来源: 评论
A robust identification approach to gait recognition
A robust identification approach to gait recognition
收藏 引用
26th ieee conference on computer vision and pattern recognition, cvpr
作者: Tao, Ding Pennsylvania State University University Park PA 16802 United States
In this paper we address the problem of human gait recognition from a robust identification and model (in)validation prospective. the main idea is to apply dimensionality reduction technique to extract the spatio-temp... 详细信息
来源: 评论