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检索条件"任意字段=2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023"
3320 条 记 录,以下是3221-3230 订阅
排序:
Hybrid User-Independent and User-Dependent Offline Signature Verification with a Two-Channel CNN  31
Hybrid User-Independent and User-Dependent Offline Signature...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Yilmaz, Mustafa Berkay Ozturk, Kagan Akdeniz Univ Antalya Turkey
Signature verification task needs relevant signature representations to achieve low error rates. Many signature representations have been proposed so far. In this work we propose a hybrid user-independent/dependent of... 详细信息
来源: 评论
Merging Deep Neural Networks for Mobile Devices  31
Merging Deep Neural Networks for Mobile Devices
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chou, Yi-Min Chan, Yi-Ming Lee, Jia-Hong Chiu, Chih-Yi Chen, Chu-Song Acad Sinica Inst Informat Sci Taipei Taiwan MOST Joint Res Ctr AI Technol & Vista Healthcare Taipei Taiwan Natl Chiayi Univ 300 Syuefu Rd Chiayi Taiwan
In this paper, a novel method to merge convolutional neural networks for the inference stage is introduced. When two feed-forward networks already trained for handling different tasks are given, our method can align t... 详细信息
来源: 评论
SqueezeNext: Hardware-Aware Neural Network Design  31
SqueezeNext: Hardware-Aware Neural Network Design
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Gholami, Amir Kwon, Kiseok Wu, Bichen Tai, Zizheng Yue, Xiangyu Jin, Peter Zhao, Sicheng Keutzer, Kurt Univ Calif Berkeley EECS Berkeley CA 94720 USA
One of the main barriers for deploying neural networks on embedded systems has been large memory and power consumption of existing neural networks. In this work, we introduce SqueezeNext, a new family of neural networ... 详细信息
来源: 评论
Deep-BCN: Deep networks meet biased competition to create a brain-inspired model of attention control  31
Deep-BCN: Deep networks meet biased competition to create a ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Adeli, Hossein Zelinsky, Gregory SUNY Stony Brook Stony Brook NY 11794 USA
The mechanism of attention control is best described by biased-competition theory (BCT), which suggests that a top-down goal state biases a competition among object representations for the selective routing of a visua... 详细信息
来源: 评论
Unsupervised Person Re-Identification with Iterative Self-Supervised Domain Adaptation
Unsupervised Person Re-Identification with Iterative Self-Su...
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ieee/cvf conference on computer vision and pattern recognition workshops
作者: Haotian Tang Yiru Zhao Hongtao Lu Key Lab of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University
In real applications, person re-identification (re-id) is an inherently domain adaptive computer vision task which often requires the model trained on a group of people to perform well on an unlabeled dataset consisti... 详细信息
来源: 评论
Multimodal 2D and 3D for In-the-wild Facial Expression recognition
Multimodal 2D and 3D for In-the-wild Facial Expression Recog...
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ieee/cvf conference on computer vision and pattern recognition workshops
作者: Son Thai Ly Nhu-Tai Do Guee-Sang Lee Soo-Hyung Kim Hyung-Jeong Yang Department of Electronics and Computer Engineering Chonnam National University
In this paper, unlike other in-the-wild facial expression recognition (FER) studies which only focused on 2D information, we present a fusion approach for 2D and 3D facial data in FER. In particular, the 3D facial dat... 详细信息
来源: 评论
WiCV 2019: The Sixth Women In computer vision Workshop
WiCV 2019: The Sixth Women In Computer Vision Workshop
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Irene Amerini Elena Balashova Sayna Ebrahimi Kathryn Leonard Arsha Nagrani Amaia Salvador University of Florence Princeton University UC Berkeley Occidental College University of Oxford Universitat Politcnica de Catalunya
In this paper we present the Women in computer vision Workshop - WiCV 2019, organized in conjunction with CVPR 2019. This event is meant for increasing the visibility and inclusion of women researchers in computer vis... 详细信息
来源: 评论
On the Suitability of Lp-norms for Creating and Preventing Adversarial Examples  31
On the Suitability of <i>L<sub>p</sub></i>-norms for Creatin...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Sharif, Mahmood Bauer, Lujo Reiter, Michael K. Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ N Carolina Chapel Hill NC 27515 USA
Much research has been devoted to better understanding adversarial examples, which are specially crafted inputs to machine-learning models that are perceptually similar to benign inputs, but are classified differently... 详细信息
来源: 评论
Aggregating Deep Pyramidal Representations for Person Re-Identification
Aggregating Deep Pyramidal Representations for Person Re-Ide...
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ieee/cvf conference on computer vision and pattern recognition workshops
作者: Niki Martinel Gian Luca Foresti Christian Micheloni Machine Learning and Perception Lab/Artificial Vision and Real-Time Systems Lab University of Udine
Learning discriminative, view-invariant and multi-scale representations of person appearance with different semantic levels is of paramount importance for person Re-Identification (Re-ID). A surge of effort has been s... 详细信息
来源: 评论
Dual-Mode Vehicle Motion pattern Learning for High Performance Road Traffic Anomaly Detection  31
Dual-Mode Vehicle Motion Pattern Learning for High Performan...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Xu, Yan Ouyang, Xi Cheng, Yu Yu, Shining Xiong, Lin Ng, Choon-Ching Pranata, Sugiri Shen, Shengmei Xing, Junliang Panasonic R&D Ctr Singapore Singapore Singapore Huazhong Univ Sci & Technol Wuhan Hubei Peoples R China Nanyang Technol Univ Singapore Singapore Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China
Anomaly detection on road traffic is an important task due to its great potential in urban traffic management and road safety. It is also a very challenging task since the abnormal event happens very rarely and exhibi... 详细信息
来源: 评论