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检索条件"任意字段=2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009"
20951 条 记 录,以下是4991-5000 订阅
排序:
Convolutional neural network architecture for geometric matching  30
Convolutional neural network architecture for geometric matc...
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30th ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Rocco, Ignacio Arandjelovic, Relja Sivic, Josef DI ENS Paris France INRIA Villeneuve Dascq France CIIRC Prague Czech Republic PSL Res Univ ENS Dept Informat CNRS F-75005 Paris France Czech Tech Univ Czech Inst Informat Robot & Cybernet Prague Czech Republic DeepMind London England
We address the problem of determining correspondences between two images in agreement with a geometric model such as an affine or thin-plate spline transformation, and estimating its parameters. The contributions of t... 详细信息
来源: 评论
Intrinsic Physical Concepts Discovery with Object-Centric Predictive Models
Intrinsic Physical Concepts Discovery with Object-Centric Pr...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Tang, Qu Zhu, Xiangyu Lei, Zhen Zhang, Zhaoxiang Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Chinese Acad Sci Inst Automat MAIS Beijing Peoples R China Chinese Acad Sci Hong Kong Inst Sci & Innovat Ctr Artificial Intelligence & Robot Beijing Peoples R China
The ability to discover abstract physical concepts and understand how they work in the world through observing lies at the core of human intelligence. The acquisition of this ability is based on compositionally percei... 详细信息
来源: 评论
Uncertainty-Aware Adaptation for Self-Supervised 3D Human Pose Estimation
Uncertainty-Aware Adaptation for Self-Supervised 3D Human Po...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kundu, Jogendra Nath Seth, Siddharth Pradyumna, Y. M. Jampani, Varun Chakraborty, Anirban Babu, R. Venkatesh Indian Inst Sci Bangalore Karnataka India Google Res Mountain View CA USA
The advances in monocular 3D human pose estimation are dominated by supervised techniques that require large-scale 2D/3D pose annotations. Such methods often behave erratically in the absence of any provision to disca... 详细信息
来源: 评论
Edge-Labeling Graph Neural Network for Few-shot Learning  32
Edge-Labeling Graph Neural Network for Few-shot Learning
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32nd ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kim, Jongmin Kim, Taesup Kim, Sungwoong Yoo, Chang D. Korea Adv Inst Sci & Technol Daejeon South Korea Univ Montreal MILA Montreal PQ Canada Kakao Brain Jeju City South Korea
In this paper, we propose a novel edge-labeling graph neural network (EGNN), which adapts a deep neural network on the edge-labeling graph, for few-shot learning. The previous graph neural network (GNN) approaches in ... 详细信息
来源: 评论
Rope3D: The Roadside Perception Dataset for Autonomous Driving and Monocular 3D Object Detection Task
Rope3D: The Roadside Perception Dataset for Autonomous Drivi...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Ye, Xiaoqing Shu, Mao Li, Hanyu Shi, Yifeng Li, Yingying Wang, Guangjie Tan, Xiao Ding, Errui Baidu Inc Beijing Peoples R China China Univ Min & Technol Beijing Peoples R China
Concurrent perception datasets for autonomous driving are mainly limited to frontal view with sensors mounted on the vehicle. None of them is designed for the overlooked roadside perception tasks. On the other hand, t... 详细信息
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Action snippets: How many frames does human action recognition require?
Action snippets: How many frames does human action recogniti...
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ieee conference on computer vision and pattern recognition
作者: Schindler, Konrad van Gool, Luc Swiss Fed Inst Technol BIWI Zurich Switzerland Katholieke Univ Leuven ESAT Leuven Belgium
Visual recognition of human actions in video clips has been an active field of research in recent years. However, most published methods either analyse an entire video and assign it a single action label, or use relat... 详细信息
来源: 评论
Exploring Adversarial Fake Images on Face Manifold
Exploring Adversarial Fake Images on Face Manifold
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Li, Dongze Wang, Wei Fan, Hongxing Dong, Jing Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China CASIA Ctr Res Intelligent Percept & Comp Beijing Peoples R China
Images synthesized by powerful generative adversarial network (GAN) based methods have drawn moral and privacy concerns. Although image forensic models have reached great performance in detecting fake images from real... 详细信息
来源: 评论
Compacting Binary Neural Networks by Sparse Kernel Selection
Compacting Binary Neural Networks by Sparse Kernel Selection
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wang, Yikai Huang, Wenbing Dong, Yinpeng Sun, Fuchun Yao, Anbang Tsinghua Univ Dept Comp Sci & Technol State Key Lab Intelligent Technol & Syst BNRist Ctr Beijing Peoples R China Renmin Univ China Gaoling Sch Artificial Intelligence Suzhou Peoples R China RealAI Shenzhen Peoples R China Intel Labs China Shenzhen Peoples R China
Binary Neural Network (BNN) represents convolution weights with 1-bit values, which enhances the efficiency of storage and computation. This paper is motivated by a previously revealed phenomenon that the binary kerne... 详细信息
来源: 评论
Prompting vision Foundation Models for Pathology Image Analysis
Prompting Vision Foundation Models for Pathology Image Analy...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Yin, Chong Liu, Siqi Zhou, Kaiyang Wong, Vincent Wai-Sun Yuen, Pong C. Hong Kong Baptist Univ Dept Comp Sci Hong Kong Peoples R China Chinese Univ Hong Kong Shenzhen Res Inst Big Data Shenzhen Peoples R China Chinese Univ Hong Kong Dept Med & Therapeut Hong Kong Peoples R China
The rapid increase in cases of non-alcoholic fatty liver disease (NAFLD) in recent years has raised significant public concern. Accurately identifying tissue alteration regions is crucial for the diagnosis of NAFLD, b... 详细信息
来源: 评论
When Does Contrastive Visual Representation Learning Work?
When Does Contrastive Visual Representation Learning Work?
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Cole, Elijah Yang, Xuan Wilber, Kimberly Mac Aodha, Oisin Belongie, Serge CALTECH Pasadena CA 91125 USA Google Mountain View CA 94043 USA Univ Edinburgh Edinburgh Midlothian Scotland Alan Turing Inst London England Univ Copenhagen Copenhagen Denmark
Recent self-supervised representation learning techniques have largely closed the gap between supervised and unsupervised learning on ImageNet classification. While the particulars of pretraining on ImageNet are now r... 详细信息
来源: 评论