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检索条件"任意字段=2006 Conference on Computer Vision and Pattern Recognition Workshops"
5506 条 记 录,以下是561-570 订阅
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BigDetection: A Large-scale Benchmark for Improved Object Detector Pre-training
BigDetection: A Large-scale Benchmark for Improved Object De...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cai, Likun Zhang, Zhi Zhu, Yi Zhang, Li Li, Mu Xue, Xiangyang Fudan Univ Shanghai Peoples R China Amazon Inc Seattle WA USA
Multiple datasets and open challenges for object detection have been introduced in recent years. To build more general and powerful object detection systems, in this paper, we construct a new large-scale benchmark ter... 详细信息
来源: 评论
Texture Complexity based Redundant Regions Ranking for Object Proposal  29
Texture Complexity based Redundant Regions Ranking for Objec...
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29th IEEE conference on computer vision and pattern recognition (CVPR)
作者: Ke, Wei Zhang, Tianliang Chen, Jie Wan, Fang Ye, Qixiang Han, Zhenjun Univ Chinese Acad Sci Beijing Peoples R China Univ Oulu CMV SF-90100 Oulu Finland
Object proposal has been successfully applied in recent visual object detection approaches and shown improved computational efficiency. The purpose of object proposal is to use as few as regions to cover as many as ob... 详细信息
来源: 评论
Assistive Signals for Deep Neural Network Classifiers
Assistive Signals for Deep Neural Network Classifiers
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Pestana, Camilo Liu, Wei Glance, David Owens, Robyn Mian, Ajmal Univ Western Australia 35 Stirling Hwy Crawley WA 6009 Australia
Deep Neural Networks are brittle in that small changes in the input can drastically affect their prediction outcome and confidence. Consequently, research in this area mainly focus on adversarial attacks and defenses.... 详细信息
来源: 评论
Learning to predict crop type from heterogeneous sparse labels using meta-learning
Learning to predict crop type from heterogeneous sparse labe...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Tseng, Gabriel Kerner, Hannah Nakalembe, Catherine Becker-Reshef, Inbal NASA Harvest College Pk MD 20742 USA Univ Maryland College Pk MD 20742 USA
There are many labelled datasets relating to land cover and crop type mapping that cover diverse geographies, agroecologies and land uses. However, these labels are often extremely sparse, particularly in low- and mid... 详细信息
来源: 评论
Multi-Scale Selective Residual Learning for Non-Homogeneous Dehazing
Multi-Scale Selective Residual Learning for Non-Homogeneous ...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Jo, Eunsung Sim, Jae-Young Ulsan Natl Inst Sci & Technol Grad Sch Artificial Intelligence Ulsan South Korea Ulsan Natl Inst Sci & Technol Dept Elect Engn Ulsan South Korea
As the particles in hazy medium cause the absorption and scattering of light, the images captured under such environment suffer from quality degradation such as low contrast and color distortion. While numerous single... 详细信息
来源: 评论
Towards autonomous navigation of miniature UAV
Towards autonomous navigation of miniature UAV
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27th IEEE conference on computer vision and pattern recognition (CVPR)
作者: Brockers, Roland Humenberger, Martin Weiss, Stephan Matthies, Larry Jet Prop Lab Pasadena CA 91109 USA Austrian Inst Technol Vienna Austria
Micro air vehicles such as miniature rotorcrafts require high-precision and fast localization updates for their control, but cannot carry large payloads. Therefore, only small and light-weight sensors and processing u... 详细信息
来源: 评论
Detection of Distracted Driver using Convolutional Neural Network  31
Detection of Distracted Driver using Convolutional Neural Ne...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Baheti, Bhakti Gajre, Suhas Talbar, Sanjay SGGS Inst Engn & Technol Ctr Excellence Signal & Image Proc Nanded Maharashtra India
Number of road accidents is continuously increasing in last few years worldwide. As per the survey of National Highway Traffic Safety Administrator, nearly one in five motor vehicle crashes are caused by distracted dr... 详细信息
来源: 评论
Understanding Knowledge Gaps in Visual Question Answering: Implications for Gap Identification and Testing
Understanding Knowledge Gaps in Visual Question Answering: I...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Bajaj, Goonmeet Bandyopadhyay, Bortik Schmidt, Daniel Maneriker, Pranav Myers, Christopher Parthasarathy, Srinivasan Ohio State Univ OSU Columbus OH 43210 USA Wright State Univ Dayton OH 45435 USA Air Force Res Lab AFRL Wright Patterson AFB OH USA
Traditional Visual Question Answering (VQA) datasets typically contain questions related to the spatial information of objects, object attributes, or general scene questions. Recently, researchers have recognized the ... 详细信息
来源: 评论
VSpSR: Explorable Super-Resolution via Variational Sparse Representation
VSpSR: Explorable Super-Resolution via Variational Sparse Re...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhou, Hangqi Huang, Chao Gao, Shangqi Zhuang, Xiahai Fudan Univ Sch Data Sci Shanghai Peoples R China
Super-resolution (SR) is an ill-posed problem, which means that infinitely many high-resolution (HR) images can be degraded to the same low-resolution (LR) image. To study the one-to-many stochastic SR mapping, we imp... 详细信息
来源: 评论
Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner
Training Domain-invariant Object Detector Faster with Featur...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Lee, Chaehyeon Seo, Junghoon Jung, Heechul Kyungpook Natl Univ Dept Artificial Intelligence Daegu South Korea SI Analyt Co Ltd Daejeon South Korea SI Analyt Daejeon South Korea
In deep learning-based object detection on remote sensing domain, nuisance factors, which affect observed variables while not affecting predictor variables, often matters because they cause domain changes. Previously,... 详细信息
来源: 评论