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检索条件"任意字段=1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992"
6449 条 记 录,以下是421-430 订阅
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Computing 3D object parts from similarities among object views
Computing 3D object parts from similarities among object vie...
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ieee conference on computer vision and pattern recognition (cvpr 2000)
作者: Cutzu, F Univ Toronto Dept Comp Sci Toronto ON M5S 3G4 Canada
The following shape segmentation problem is addressed: find the part decomposition of a 3D object that accounts for an observed pattern of similarities among several of the object's views. This represents the inve... 详细信息
来源: 评论
A Compact Deep Learning Model for Robust Facial Expression recognition  31
A Compact Deep Learning Model for Robust Facial Expression R...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kuo, Chieh-Ming Lai, Shang-Hong Sarkis, Michel Natl Tsing Hua Univ Hsinchu Taiwan Qualcomm Technol Inc San Diego CA USA
In this paper, we propose a compact frame-based facial expression recognition framework for facial expression recognition which achieves very competitive performance with respect to state-of-the-art methods while usin... 详细信息
来源: 评论
Soft-margin learning for multiple feature-kernel combinations with Domain Adaptation, for recognition in surveillance face datasets  29
Soft-margin learning for multiple feature-kernel combination...
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29th ieee conference on computer vision and pattern recognition (cvpr)
作者: Banerjee, Samik Das, Sukhendu IIT Madras Madras 600036 Tamil Nadu India
Face recognition (FR) is the most preferred mode for biometric-based surveillance, due to its passive nature of detecting subjects, amongst all different types of biometric traits. FR under surveillance scenario does ... 详细信息
来源: 评论
Pixel-Guided Dual-Branch Attention Network for Joint Image Deblurring and Super-Resolution
Pixel-Guided Dual-Branch Attention Network for Joint Image D...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Xi, Si Wei, Jia Zhang, Weidong Netease Games AI Lab Hangzhou Peoples R China
Image deblurring and super-resolution (SR) are computer vision tasks aiming to restore image detail and spatial scale, respectively. Besides, only a few recent works of literature contribute to this task, as conventio... 详细信息
来源: 评论
A factorization method for affine structure from line correspondences
A factorization method for affine structure from line corres...
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1966 ieee computer society conference on computer vision and pattern recognition
作者: Quan, L Kanade, T CARNEGIE MELLON UNIV INST ROBOTPITTSBURGHPA 15213
A family of structure from motion algorithms called the factorization method has been recently developed from the orthographic projection model to the affine camera model [23, 16, 18]. All these algorithms are limited... 详细信息
来源: 评论
Comparison of deep transfer learning strategies for digital pathology  31
Comparison of deep transfer learning strategies for digital ...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Mormont, Romain Geurts, Pierre Maree, Raphael Univ Liege Liege Belgium
In this paper, we study deep transfer learning as a way of overcoming object recognition challenges encountered in the field of digital pathology. Through several experiments, we investigate various uses of pre-traine... 详细信息
来源: 评论
DETECTION OF BUILDINGS USING PERCEPTUAL GROUPING AND SHADOWS
DETECTION OF BUILDINGS USING PERCEPTUAL GROUPING AND SHADOWS
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1994 ieee computer-society conference on computer vision and pattern recognition
作者: LIN, C HUERTAS, A NEVATIA, R UNIV SO CALIF INST ROBOT & INTELLIGENT SYSTLOS ANGELESCA 90089
We described a system for detection and description of buildings in aerial scenes. This is a difficult task as the aerial images contain a variety of objects. Low-level segmentation processes give highly fragmented se... 详细信息
来源: 评论
TAL EmotioNet Challenge 2020 Rethinking the Model Chosen Problem in Multi-Task Learning
TAL EmotioNet Challenge 2020 Rethinking the Model Chosen Pro...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wang, Pengcheng Wang, Zihao Ji, Zhilong Liu, Xiao Yang, Songfan Wu, Zhongqin TAL Educ Grp Beijing Peoples R China
This paper introduces our approach to the EmotioNet Challenge 2020. We pose the AU recognition problem as a multi-task learning problem, where the non-rigid facial muscle motion (mainly the first 17 AUs) and the rigid... 详细信息
来源: 评论
Learning to form large groups of salient image features
Learning to form large groups of salient image features
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1998 ieee computer-society conference on computer vision and pattern recognition
作者: Sarkar, S Univ S Florida Tampa FL 33620 USA
We offer a novel strategy to adapt the perceptual organization process to an object and its context in a scene. Given a set of training images of an object in context, a learning process decides on the relative import... 详细信息
来源: 评论
Shadow Removal with Paired and Unpaired Learning
Shadow Removal with Paired and Unpaired Learning
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Vasluianu, Florin-Alexandru Romero, Andres Van Gool, Luc Timofte, Radu Swiss Fed Inst Technol Zurich Switzerland
Shadow removal is an important computer vision task aiming at the detection and successful removal of the shadow produced by an occluded light source and a photorealistic restoration of the image contents. Decades of ... 详细信息
来源: 评论