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检索条件"任意字段=1994 IEEE Computer-Society Conference on Computer Vision and Pattern Recognition"
22906 条 记 录,以下是4741-4750 订阅
排序:
Maximum-likelihood template matching
Maximum-likelihood template matching
收藏 引用
ieee conference on computer vision and pattern recognition, CVPR 2000
作者: Olson, Clark F. California Inst of Technology Pasadena CA United States
In image matching applications such as tracking and stereo matching, it is common to use the sum-of-squared-differences (SSD) measure to determine the best match for an image template. However, this measure is sensiti... 详细信息
来源: 评论
Bootstrapping ViTs: Towards Liberating vision Transformers from Pre-training
Bootstrapping ViTs: Towards Liberating Vision Transformers f...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Haofei Duan, Jiarui Xue, Mengqi Song, Jie Sun, Li Song, Mingli Zhejiang Univ Hangzhou Zhejiang Peoples R China Zhejiang Univ Shanghai Inst Adv Study Hangzhou Zhejiang Peoples R China
Recently, vision Transformers (ViTs) are developing rapidly and starting to challenge the domination of convolutional neural networks (CNNs) in the realm of computer vision (CV). With the general-purpose Transformer a... 详细信息
来源: 评论
Know Your Neighbors: Improving Single-View Reconstruction via Spatial vision-Language Reasoning
Know Your Neighbors: Improving Single-View Reconstruction vi...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Li, Rui Fischer, Tobias Segu, Mattia Pollefeys, Marc Van Gool, Luc Tombari, Federico Swiss Fed Inst Technol Zurich Switzerland Google Mountain View CA 94043 USA Tech Univ Munich Munich Germany
Recovering the 3D scene geometry from a single view is a fundamental yet ill-posed problem in computer vision. While classical depth estimation methods infer only a 2.5D scene representation limited to the image plane... 详细信息
来源: 评论
Transferability Metrics for Selecting Source Model Ensembles
Transferability Metrics for Selecting Source Model Ensembles
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Agostinelli, Andrea Uijlings, Jasper Mensink, Thomas Ferrari, Vittorio Google Res Mountain View CA 94043 USA
We address the problem of ensemble selection in transfer learning: Given a large pool of source models we want to select an ensemble of models which, after fine-tuning on the target training set, yields the best perfo... 详细信息
来源: 评论
Autoregressive Stylized Motion Synthesis with Generative Flow
Autoregressive Stylized Motion Synthesis with Generative Flo...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wen, Yu-Hui Yang, Zhipeng Fu, Hongbo Gao, Lin Sun, Yanan Liu, Yong-Jin Tsinghua Univ BNRist CS Dept Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China City Univ Hong Kong Sch Creat Media Hong Kong Peoples R China Chinese Acad Sci Beijing Key Lab Mobile Comp & Pervas Device ICT Beijing Peoples R China
Motion style transfer is an important problem in many computer graphics and computer vision applications, including human animation, games, and robotics. Most existing deep learning methods for this problem are superv... 详细信息
来源: 评论
Space-sweep approach to true multi-image matching
Space-sweep approach to true multi-image matching
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Proceedings of the 1996 ieee computer society conference on computer vision and pattern recognition
作者: Collins, Robert T. Univ of Massachusetts Amherst United States
The problem of determining feature correspondences across multiple views is considered. The term 'true multi-image' matching is introduced to describe techniques that make full and efficient use of the geometr... 详细信息
来源: 评论
Learning Placeholders for Open-Set recognition
Learning Placeholders for Open-Set Recognition
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhou, Da-Wei Ye, Han-Jia Zhan, De-Chuan Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China
Traditional classifiers are deployed under closed-set setting, with both training and test classes belong to the same set. However, real-world applications probably face the input of unknown categories, and the model ... 详细信息
来源: 评论
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
Style-based Point Generator with Adversarial Rendering for P...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xie, Chulin Wang, Chuxin Zhang, Bo Yang, Hao Chen, Dong Wen, Fang Univ Illinois Champaign IL 61820 USA Univ Sci & Technol China Hefei Anhui Peoples R China Microsoft Res Asia Beijing Peoples R China
In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion. Firstly, we present the channel-attentive EdgeConv to fully exploit the local structures... 详细信息
来源: 评论
Masked-attention Mask Transformer for Universal Image Segmentation
Masked-attention Mask Transformer for Universal Image Segmen...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Cheng, Bowen Misra, Ishan Schwing, Alexander G. Kirillov, Alexander Girdhar, Rohit Facebook AI Res FAIR Menlo Pk CA 94025 USA Univ Illinois Urbana Champaign UIUC Champaign IL 61820 USA
Image segmentation groups pixels with different semantics, e.g., category or instance membership. Each choice of semantics defines a task. While only the semantics of each task differ, current research focuses on desi... 详细信息
来源: 评论
Actor and Observer: Joint Modeling of First and Third-Person Videos  31
Actor and Observer: Joint Modeling of First and Third-Person...
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31st ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Sigurdsson, Gunnar A. Gupta, Abhinav Schmid, Cordelia Farhadi, Ali Alahari, Karteek Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Grenoble Alpes INRIA CNRS Grenoble INPLJK F-38000 Grenoble France Allen Inst Artificial Intelligence Seattle WA USA INRIA Grenoble France
Several theories in cognitive neuroscience suggest that when people interact with the world, or simulate interactions, they do so from a first-person egocentric perspective, and seamlessly transfer knowledge between t... 详细信息
来源: 评论