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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291-300 订阅
排序:
Fine-Grained recognition without Part Annotations
Fine-Grained Recognition without Part Annotations
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ieee conference on computer vision and pattern recognition (cvpr)
作者: Krause, Jonathan Jin, Hailin Yang, Jianchao Li Fei-Fei Stanford Univ Stanford CA 94305 USA Adobe Res San Jose CA USA
Scaling up fine-grained recognition to all domains of fine-grained objects is a challenge the computer vision community will need to face in order to realize its goal of recognizing all object categories. Current stat... 详细信息
来源: 评论
Transparent Object Reconstruction via Coded Transport of Intensity  27
Transparent Object Reconstruction via Coded Transport of Int...
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27th ieee conference on computer vision and pattern recognition (cvpr)
作者: Ma, Chenguang Lin, Xing Suo, Jinli Dai, Qionghai Wetzstein, Gordon Tsinghua Univ Dept Automat Beijing Peoples R China
Capturing and understanding visual signals is one of the core interests of computer vision. Much progress has been made w.r.t. many aspects of imaging, but the reconstruction of refractive phenomena, such as turbulenc... 详细信息
来源: 评论
CoMoGAN: continuous model-guided image-to-image translation
CoMoGAN: continuous model-guided image-to-image translation
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Pizzati, Fabio Cerri, Pietro de Charette, Raoul INRIA Vislab Le Chesnay Rocquencourt France Vislab Parma Pr Italy INRIA Le Chesnay Rocquencourt France
CoMoGAN is a continuous GAN relying on the unsupervised reorganization of the target data on a functional manifold. To that matter, we introduce a new Functional Instance Normalization layer and residual mechanism, wh... 详细信息
来源: 评论
Closest point search in high dimensions
Closest point search in high dimensions
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1966 ieee computer Society conference on computer vision and pattern recognition
作者: Nene, SA Nayar, SK COLUMBIA UNIV DEPT COMP SCINEW YORKNY 10027
The problem of finding the closest point in high-dimensional spaces is common in computational vision. Unfortunately, the complexity of most existing search algorithms, such as k-d tree and R-tree, grows exponentially... 详细信息
来源: 评论
Video browsing using edges and motion
Video browsing using edges and motion
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1966 ieee computer Society conference on computer vision and pattern recognition
作者: Zabih, R Miller, J Mai, K CORNELL UNIV DEPT COMP SCIITHACANY 14853
Automatic video browsing requires algorithms for detecting a variety of events, including production effects (e.g., scene breaks and captions) and moving objects. We present new methods that use edges and motion for d... 详细信息
来源: 评论
Viewpoint variation in the noise sensitivity of pose estimation
Viewpoint variation in the noise sensitivity of pose estimat...
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1966 ieee computer Society conference on computer vision and pattern recognition
作者: Madsen, CB AALBORG UNIV INST ELECT SYSTLAB IMAGE ANALDK-9220 AALBORG ODENMARK
The paper presents an analysis of the stability of pose estimation. The investigated pose estimation technique is based on orientations of three edge segments and provides the rotation part of object pose. The specifi... 详细信息
来源: 评论
Probabilistic Label Trees for Efficient Large Scale Image Classification
Probabilistic Label Trees for Efficient Large Scale Image Cl...
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26th ieee conference on computer vision and pattern recognition (cvpr)
作者: Liu, Baoyuan Sadeghi, Fereshteh Tappen, Marshall Shamir, Ohad Liu, Ce Univ Cent Florida Orlando FL 32816 USA Microsoft Res Boston NE USA
Large-scale recognition problems with thousands of classes pose a particular challenge because applying the classifier requires more computation as the number of classes grows. The label tree model integrates classifi... 详细信息
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Motion of disturbances: Detection and tracking of multi-body non-rigid motion
Motion of disturbances: Detection and tracking of multi-body...
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1997 ieee computer Society conference on computer vision and pattern recognition (cvpr 97)
作者: Halevi, G Weinshall, D HEBREW UNIV JERUSALEM INST COMP SCIIL-91904 JERUSALEMISRAEL
We present a new approach to the tracking of very non rigid patterns of motion, such as water flowing down a stream. The algorithm is based on a ''disturbance map,'' which is obtained by linearly subtr... 详细信息
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Skeleton-based Dynamic hand gesture recognition  29
Skeleton-based Dynamic hand gesture recognition
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29th ieee conference on computer vision and pattern recognition (cvpr)
作者: De Smedt, Quentin Wannous, Hazem Vandeborre, Jean-Philippe Univ Lille Telecom Lille CNRS UMR 9189CRIStAL F-59000 Lille France
In this paper, a new skeleton-based approach is proposed for 3D hand gesture recognition. Specifically, we exploit the geometric shape of the hand to extract an effective descriptor from hand skeleton connected joints... 详细信息
来源: 评论
Embedding Sequential Information into Spatiotemporal Features for Action recognition  29
Embedding Sequential Information into Spatiotemporal Feature...
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29th ieee conference on computer vision and pattern recognition (cvpr)
作者: Ye, Yuancheng Tian, Yingli CUNY Grad Ctr New York NY 10021 USA CUNY City Coll New York NY 10021 USA
In this paper, we introduce a novel framework for video-based action recognition, which incorporates the sequential information with the spatiotemporal features. Specifically, the spatiotemporal features are extracted... 详细信息
来源: 评论