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检索条件"任意字段=2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016"
21008 条 记 录,以下是321-330 订阅
排序:
Combination of multiple classifiers using local accuracy estimates
Combination of multiple classifiers using local accuracy est...
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1966 ieee computer Society conference on computer vision and pattern recognition
作者: Woods, K Bowyer, K Kegelmeyer, WP UNIV S FLORIDA DEPT COMP ENGN & SCITAMPAFL 33620
Combination of Multiple Classifiers (CMC) has recently drawn attention as a method of improving classification accuracy. This paper presents a method for combining classifiers that uses estimates of each individual cl... 详细信息
来源: 评论
Anytime recognition of Objects and Scenes  27
Anytime Recognition of Objects and Scenes
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27th ieee conference on computer vision and pattern recognition (cvpr)
作者: Karayev, Sergey Fritz, Mario Darrell, Trevor Univ Calif Berkeley Berkeley CA 94720 USA Max Planck Inst Informat Saarbrucken Germany
Humans are capable of perceiving a scene at a glance, and obtain deeper understanding with additional time. Similarly, visual recognition deployments should be robust to varying computational budgets. Such situations ... 详细信息
来源: 评论
A Hough Transform-Based Voting Framework for Action recognition
A Hough Transform-Based Voting Framework for Action Recognit...
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23rd ieee conference on computer vision and pattern recognition (cvpr)
作者: Yao, Angela Gall, Juergen Van Gool, Luc ETH Zurich Switzerland
We present a method to classify and localize human actions in video using a Hough transform voting framework. Random trees are trained to learn a mapping between densely-sampled feature patches and their corresponding... 详细信息
来源: 评论
Recognizing Human Actions from Still Images with Latent Poses
Recognizing Human Actions from Still Images with Latent Pose...
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23rd ieee conference on computer vision and pattern recognition (cvpr)
作者: Yang, Weilong Wang, Yang Mori, Greg Simon Fraser Univ Sch Comp Sci Burnaby BC V5A 1S6 Canada
We consider the problem of recognizing human actions from still images. We propose a novel approach that treats the pose of the person in the image as latent variables that will help with recognition. Different from o... 详细信息
来源: 评论
Learning RoI Transformer for Oriented Object Detection in Aerial Images  32
Learning RoI Transformer for Oriented Object Detection in Ae...
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32nd ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Ding, Jian Xue, Nan Long, Yang Xia, Gui-Song Lu, Qikai Wuhan Univ LIESMARS CAPTAIN Wuhan 430079 Peoples R China
Object detection in aerial images is an active yet challenging task in computer vision because of the bird's-eye view perspective, the highly complex backgrounds, and the variant appearances of objects. Especially... 详细信息
来源: 评论
Recovering affine motion and defocus blur simultaneously
Recovering affine motion and defocus blur simultaneously
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1966 ieee computer Society conference on computer vision and pattern recognition
作者: Myles, Z Lobo, ND UNIV CENT FLORIDA DEPT COMP SCIORLANDOFL 32816
There are at least two situations in practical computer vision where displacement of a point in an image is accompanied by a defocus blur. The first is when a camera of limited autofocal capability moves in depth, and... 详细信息
来源: 评论
Noising versus Smoothing for Vertex Identification in Unknown Shapes  27
Noising versus Smoothing for Vertex Identification in Unknow...
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27th ieee conference on computer vision and pattern recognition (cvpr)
作者: Raftopoulos, Konstantinos A. Ferecatu, Marin CNAM Ctr Etud & Rech Informat & Commun CEDRIC FR-75141 Paris 03 France
A method for identifying shape features of local nature on the shapes boundary, in a way that is facilitated by the presence of noise is presented. The boundary is seen as a real function. A study of a certain distanc... 详细信息
来源: 评论
Towards Long-Form Video Understanding
Towards Long-Form Video Understanding
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wu, Chao-Yuan Krahenbuhl, Philipp Univ Texas Austin Austin TX 78712 USA
Our world offers a never-ending stream of visual stimuli, yet today's vision systems only accurately recognize patterns within a few seconds. These systems understand the present, but fail to contextualize it in p... 详细信息
来源: 评论
OSKDet: Orientation-sensitive Keypoint Localization for Rotated Object Detection
OSKDet: Orientation-sensitive Keypoint Localization for Rota...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Lu, Dongchen Li, Dongmei Li, Yali Wang, Shengjin Tsinghua Univ Dept Elect Engn Beijing Peoples R China
Rotated object detection is a challenging issue in computer vision field. Inadequate rotated representation and the confusion of parametric regression have been the bottleneck for high performance rotated detection. I... 详细信息
来源: 评论
Multi-View Feature Engineering and Learning
Multi-View Feature Engineering and Learning
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ieee conference on computer vision and pattern recognition (cvpr)
作者: Dong, Jingming Karianakis, Nikolaos Davis, Damek Hernandez, Joshua Balzer, Jonathan Soatto, Stefano Univ Calif Los Angeles Vis Lab Los Angeles CA 90095 USA
We frame the problem of local representation of imaging data as the computation of minimal sufficient statistics that are invariant to nuisance variability induced by viewpoint and illumination. We show that, under ve... 详细信息
来源: 评论