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检索条件"任意字段=IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops"
8962 条 记 录,以下是351-360 订阅
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Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans
Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR S...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Kalinicheva, Ekaterina Landrieu, Loic Mallet, Clement Chehata, Nesrine Univ Gustave Eiffel LASTIG IGN ENSG F-77454 Marne La Vallee France Univ Bordeaux BIOGECO UMR 1202 INRAE Bordeaux France Univ Bordeaux Montaigne Bordeaux INP Bordeaux France
The analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across all vegetation layers, most datasets... 详细信息
来源: 评论
Dark Corner on Skin Lesion Image Dataset: Does it matter?
Dark Corner on Skin Lesion Image Dataset: Does it matter?
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Pewton, Samuel William Yap, Moi Hoon Manchester Metropolitan Univ Dept Comp & Math John Dalton Bldg Manchester M1 5GD Lancs England
Skin lesion image datasets gained popularity in recent years with the successes of ISIC datasets and challenges. While the users of these datasets are growing, the Dark Corner Artifact (DCA) phenomenon is under explor... 详细信息
来源: 评论
Continually Learning Self-Supervised Representations with Projected Functional Regularization
Continually Learning Self-Supervised Representations with Pr...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Gomez-Villa, Alex Twardowski, Bartlomiej Yu, Lu Bagdanov, Andrew D. van de Weijer, Joost Univ Autonoma Barcelona Comp Vis Ctr Barcelona Spain Tianjin Univ Technol Sch Comp Sci & Engn Tianjin Peoples R China Univ Florence MICC Florence Italy
Recent self-supervised learning methods are able to learn high-quality image representations and are closing the gap with supervised approaches. However, these methods are unable to acquire new knowledge incrementally... 详细信息
来源: 评论
Pseudo-label Generation and Various Data Augmentation for Semi-Supervised Hyperspectral Object Detection
Pseudo-label Generation and Various Data Augmentation for Se...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yu, Jun Zhang, Liwen Du, Shenshen Chang, Hao Lu, Keda Zhang, Zhong Yu, Ye Wang, Lei Ling, Qiang Univ Sci & Technol China Hefei Anhui Peoples R China Hefei ZhanDa Intelligence Technol Co Ltd Hefei Anhui Peoples R China Hefei Univ Technol Hefei Anhui Peoples R China
Semi-supervised learning is a highly researched problem, but existing semi-supervised object detection frameworks are based on RGB images, and existing pre-trained models cannot be used for hyperspectral images. To ov... 详细信息
来源: 评论
Multi-Dimensional vision Transformer Compression via Dependency Guided Gaussian Process Search
Multi-Dimensional Vision Transformer Compression via Depende...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Hou, Zejiang Kung, Sun-Yuan Princeton Univ Princeton NJ 08544 USA
vision transformers (ViT) have recently attracted considerable attentions, but the huge computational cost remains an issue for practical deployment. Previous ViT pruning methods tend to prune the model along one dime... 详细信息
来源: 评论
Visual Goal-Directed Meta-Imitation Learning
Visual Goal-Directed Meta-Imitation Learning
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Rivera, Corban G. Handelman, David A. Ratto, Christopher R. Patrone, David Paulhamus, Bart L. Johns Hopkins Univ Intelligent Syst Ctr Appl Phys Lab Laurel MD 20723 USA
The goal of meta-learning is to generalize to new tasks and goals as quickly as possible. Ideally, we would like approaches that generalize to new goals and tasks on the first attempt. Requiring a policy to perform on... 详细信息
来源: 评论
A Categorized Reflection Removal Dataset with Diverse Real-world Scenes
A Categorized Reflection Removal Dataset with Diverse Real-w...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Lei, Chenyang Huang, Xuhua Qi, Chenyang Zhao, Yankun Sun, Wenxiu Yan, Qiong Chen, Qifeng HKUST Hong Kong Peoples R China CMU Pittsburgh PA USA SenseTime Hong Kong Peoples R China
Due to the lack of a large-scale reflection removal dataset with diverse real-world scenes, many existing reflection removal methods are trained on synthetic data plus a small amount of real-world data, which makes it... 详细信息
来源: 评论
Z-Domain Entropy Adaptable Flex for Semi-supervised Action recognition in the Dark
Z-Domain Entropy Adaptable Flex for Semi-supervised Action R...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Chen, Zhi Fan, Zijun Li, Yongjie Gao, Huaien Lin, Shan Guangzhou Xi Ma Informat Technol Co 101 Waihuan Xi Rd Guangzhou 510006 Guangdong Peoples R China
The subtask of Human Action recognition (AR) in the dark is gaining a lot of traction nowadays, which takes a significant place in the field of computer vision. The implementation of its application includes self-driv... 详细信息
来源: 评论
Using Pure Pollen Species When Training a CNN to Segment Pollen Mixtures
Using Pure Pollen Species When Training a CNN to Segment Pol...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yang, Nana Joos, Victor Jacquemart, A. L. Buyens, Christel De Vleeschouwer, C. UCLouvain ICTEAM Inst Ottignies Belgium UCLouvain ELI Inst Ottignies Belgium
Recognizing the types of pollen grains and estimating their proportion in pollen mixture samples collected in a specific geographical area is important for agricultural, medical, and ecosystem research. Our paper adop... 详细信息
来源: 评论
Network Amplification with Efficient MACs Allocation
Network Amplification with Efficient MACs Allocation
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Liu, Chuanjian Han, Kai Xiao, An Nie, Ying Zhang, Wei Wang, Yunhe Huawei Noahs Ark Lab Montreal PQ Canada
Recent studies on deep convolutional neural networks present a simple paradigm of architecture design, i.e., models with more MACs typically achieve better accuracies, such as EfficientNet and RegNet. These works try ... 详细信息
来源: 评论