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检索条件"任意字段=2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2021"
3855 条 记 录,以下是3751-3760 订阅
排序:
MultiNet++: Multi-Stream Feature Aggregation and Geometric Loss Strategy for Multi-Task Learning
MultiNet++: Multi-Stream Feature Aggregation and Geometric L...
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ieee/cvf conference on computer vision and pattern recognition workshops
作者: Sumanth Chennupati Ganesh Sistu Senthil Yogamani Samir A Rawashdeh Valco North America Valeo Vision Systems University of Michigan-Dearborn
Multi-task learning is commonly used in autonomous driving for solving various visual perception tasks. It offers significant benefits in terms of both performance and computational complexity. Current work on multi-t... 详细信息
来源: 评论
Assessing Shape Bias Property of Convolutional Neural Networks  31
Assessing Shape Bias Property of Convolutional Neural Networ...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Hosseini, Hossein Xiao, Baicen Jaiswal, Mayoore Poovendran, Radha Univ Washington Dept Elect Engn NSL Seattle WA 98195 USA
It is known that humans display "shape bias" when classifying new items, i.e., they prefer to categorize objects based on their shape rather than color. Convolutional Neural Networks (CNNs) are also designed... 详细信息
来源: 评论
Empirically Analyzing the Effect of Dataset Biases on Deep Face recognition Systems  31
Empirically Analyzing the Effect of Dataset Biases on Deep F...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kortylewski, Adam Egger, Bernhard Schneider, Andreas Gerig, Thomas Morel-Forster, Andreas Vetter, Thomas Univ Basel Dept Math & Comp Sci Basel Switzerland
It is unknown what kind of biases modern in the wild face datasets have because of their lack of annotation. A direct consequence of this is that total recognition rates alone only provide limited insight about the ge... 详细信息
来源: 评论
SCAN: Spatial Color Attention Networks for Real Single Image Super-Resolution
SCAN: Spatial Color Attention Networks for Real Single Image...
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ieee/cvf conference on computer vision and pattern recognition workshops
作者: Xuan Xu Xin Li Lane Department of Computer Science and Electrical Engineering West Virginia University
Conceptually similar to adaptation in model-based approaches, attention has received increasing more attention in deep learning recently. As a tool to reallocate limited computational resources based on the importance... 详细信息
来源: 评论
Design of a Reconfigurable 3D Pixel-Parallel Neuromorphic Architecture for Smart Image Sensor  31
Design of a Reconfigurable 3D Pixel-Parallel Neuromorphic Ar...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Bhowmik, Pankaj Pantho, Jubaer Hossain Asadinia, Marjan Bobda, Christophe Univ Arkansas Fayetteville AR 72701 USA
Power reduction and speed-up of image processing algorithms remain of high interest as image resolutions continue to increase. Neuromorphic-circuits are inspired by the nervous system aiming to reduce power consumptio... 详细信息
来源: 评论
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
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