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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4581-4590 订阅
排序:
Unsupervised Domain Adaptation for Weed Segmentation Using Greedy Pseudo-labelling
Unsupervised Domain Adaptation for Weed Segmentation Using G...
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Yingchao Huang Abdul Bais University of Regina Regina Canada
Automatic weed identification based on RGB images with convolutional neural networks (CNN) is a new frontier of precision agriculture. However, the CNN models expect a large volume of labelled data. Their performance ... 详细信息
来源: 评论
Multi-User Natural Interaction System based on Real-Time Hand Tracking and Gesture recognition
Multi-User Natural Interaction System based on Real-Time Han...
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International conference on pattern recognition
作者: A. Del Bimbo L. Landucci A. Valli Universita degli Studi di Firenze Firenze Toscana IT Dipartimento di Sistemi e Informatica University of Florence Italy Firenze Italy
We present a computer vision based system that enables multiple people to interact naturally with a large display table using their own bare-hand gestures. The display presents and supports a particular multimedia app... 详细信息
来源: 评论
Non-Rigid Metric Shape and Motion Recovery from Uncalibrated Images Using Priors
Non-Rigid Metric Shape and Motion Recovery from Uncalibrated...
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conference on computer vision and pattern recognition (CVPR)
作者: A. Del Bue X. Llad L. Agapito Department of Computer Science University of London London UK
In this paper we focus on the estimation of the 3D Euclidean shape and motion of a non-rigid object which is moving rigidly while deforming and is observed by a perspective camera. Our method exploits the fact that it... 详细信息
来源: 评论
Implicit Euler ODE Networks for Single-Image Dehazing
Implicit Euler ODE Networks for Single-Image Dehazing
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Jiawei Shen Zhuoyan Li Lei Yu Gui-Song Xia Wen Yang School of Electronic and Information Wuhan University School of Computer Science Wuhan University Wuhan China
Deep convolutional neural networks (CNN) have been applied for image dehazing tasks, where the residual network (ResNet) is often adopted as the basic component to avoid the vanishing gradient problem. Recently, many ... 详细信息
来源: 评论
Wire Structure pattern Extraction and Tracking From X-Ray Images of Composite Mechanisms
Wire Structure Pattern Extraction and Tracking From X-Ray Im...
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conference on computer vision and pattern recognition (CVPR)
作者: D. Tschumperle J. Fadili GREYC IMAGE (CNRS UMR 6072) Juin Caen Cedex France
This paper introduces a complete pipeline of image processing methods in order to analyze and track the internal structures of a composite material. As a first step, input Xray images are denoised, enhanced, separated... 详细信息
来源: 评论
Discriminant Distribution-Agnostic Loss for Facial Expression recognition in the Wild
Discriminant Distribution-Agnostic Loss for Facial Expressio...
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Amir Hossein Farzaneh Xiaojun Qi Department of Computer Science Utah State University Logan UT USA
Facial Expression recognition (FER) has demonstrated remarkable progress due to the advancement of deep Convolutional Neural Networks (CNNs). FER's goal as a visual recognition problem is to learn a mapping from t... 详细信息
来源: 评论
PEA: Improving the Performance of ReLU Networks for Free by Using Progressive Ensemble Activations
PEA: Improving the Performance of ReLU Networks for Free by ...
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Á kos Utasi Continental AI Development Center Budapest
In recent years novel activation functions have been proposed to improve the performance of neural networks, and they show superior performance compared to the ReLU counterpart. However, there are environments, where ... 详细信息
来源: 评论
Is Our Continual Learner Reliable? Investigating Its Decision Attribution Stability through SHAP Value Consistency
Is Our Continual Learner Reliable? Investigating Its Decisio...
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Yusong Cai Shimou Ling Liang Zhang Lili Pan Hongliang Li University of Electronic Science and Technology of China Chengdu China
In this work, we identify continual learning (CL) methods’ inherent differences in sequential decision attribution. In the sequential learning process, inconsistent decision attribution may undermine the interpretabi... 详细信息
来源: 评论
Open-world Instance Segmentation: Top-down Learning with Bottom-up Supervision
Open-world Instance Segmentation: Top-down Learning with Bot...
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Tarun Kalluri Weiyao Wang Heng Wang Manmohan Chandraker Lorenzo Torresani Du Tran UC San Diego Meta AI
Top-down instance segmentation architectures excel with predefined closed-world taxonomies but exhibit biases and performance degradation in open-world scenarios. In this work, we introduce bottom-Up and top-Down Open... 详细信息
来源: 评论
uTRAND: Unsupervised Anomaly Detection in Traffic Trajectories
uTRAND: Unsupervised Anomaly Detection in Traffic Trajectori...
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IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)
作者: Giacomo D’Amicantonio Egor Bondarau Peter H.N De With Eindhoven University of Technology Eindhoven Netherlands
Deep learning-based approaches have achieved significant improvements on public video anomaly datasets, but often do not perform well in real-world applications. This paper addresses two issues: the lack of labeled da... 详细信息
来源: 评论