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检索条件"任意字段=2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022"
3917 条 记 录,以下是3591-3600 订阅
排序:
Deflating Dataset Bias Using Synthetic Data Augmentation
Deflating Dataset Bias Using Synthetic Data Augmentation
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Nikita Jaipuria Xianling Zhang Rohan Bhasin Mayar Arafa Punarjay Chakravarty Shubham Shrivastava Sagar Manglani Vidya N. Murali Ford Greenfield Labs Palo Alto
Deep Learning has seen an unprecedented increase in vision applications since the publication of large-scale object recognition datasets and introduction of scalable compute hardware. State-of-the-art methods for most... 详细信息
来源: 评论
The 1st Challenge on Remote Physiological Signal Sensing (RePSS)
The 1st Challenge on Remote Physiological Signal Sensing (Re...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Xiaobai Li Hu Han Hao Lu Xuesong Niu Zitong Yu Antitza Dantcheva Guoying Zhao Shiguang Shan Center for Machine Vision and Signal Analysis University of Oulu Finland Key Laboratory of Intelligient Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology China STARS team INRIA France
Remote measurement of physiological signals from videos is an emerging topic. The topic draws great interests, but the lack of publicly available benchmark databases and a fair validation platform are hindering its fu... 详细信息
来源: 评论
Improving the affordability of robustness training for DNNs
Improving the affordability of robustness training for DNNs
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Sidharth Gupta Parijat Dube Ashish Verma University of Illinois Urbana-Champaign IBM Research
Projected Gradient Descent (PGD) based adversarial training has become one of the most prominent methods for building robust deep neural network models. However, the computational complexity associated with this appro... 详细信息
来源: 评论
Upright and Stabilized Omnidirectional Depth Estimation for Wide-baseline Multi-camera Inertial Systems
Upright and Stabilized Omnidirectional Depth Estimation for ...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Changhee Won Hochang Seok Jongwoo Lim MultiplEYE Co. Ltd. Seoul Korea Department of Computer Science Hanyang University Seoul Korea
This paper presents an upright and stabilized omnidirectional depth estimation for an arbitrarily rotated wide- baseline multi-camera inertial system. By aligning the reference rig coordinate system with the gravity d... 详细信息
来源: 评论
Detecting Deepfake Videos using Attribution-Based Confidence Metric
Detecting Deepfake Videos using Attribution-Based Confidence...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Steven Fernandes Sunny Raj Rickard Ewetz Jodh Singh Pannu Sumit Kumar Jha Eddy Ortiz Iustina Vintila Margaret Salter Department of Computer Science Electrical and Computer Engineering University of Central Orlando Florida FL Solution Acceleration and Innovation Department Royal Bank of Canada
Recent advances in generative adversarial networks have made detecting fake videos a challenging task. In this paper, we propose the application of the state-of-the-art attribution based confidence (ABC) metric for de... 详细信息
来源: 评论
Learning A Meta-Ensemble Technique For Skin Lesion Classification And Novel Class Detection
Learning A Meta-Ensemble Technique For Skin Lesion Classific...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Subhranil Bagchi Anurag Banerjee Deepti R. Bathula Department of Computer Science and Engineering Indian Institute of Technology Ropar India
The frequency and fatality rates associated with skin Melanoma requires an accurate and efficient detection methodology to enable early medical diagnosis. Artificial Intelligence (AI) augmented detection methods aim a... 详细信息
来源: 评论
Reducing catastrophic forgetting with learning on synthetic data
Reducing catastrophic forgetting with learning on synthetic ...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Wojciech Masarczyk Ivona Tautkute Institute of Theoretical and Applied Informatics Polish Academy of Sciences Polish-Japanese Academy of Information Technology
Catastrophic forgetting is a problem caused by neural networks' inability to learn data in sequence. After learning two tasks in sequence, performance on the first one drops significantly. This is a serious disadv... 详细信息
来源: 评论
Moiré pattern Removal via Attentive Fractal Network
Moiré Pattern Removal via Attentive Fractal Network
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Dejia Xu Yihao Chu Qingyan Sun Peking University Beijing University of Posts and Telecommunications Beijing Jiaotong University
Moiré patterns are commonly seen artifacts when taking photos of screens and other objects with high-frequency textures. It's challenging to remove the moiré patterns considering its complex color and sh... 详细信息
来源: 评论
Yoga-82: A New Dataset for Fine-grained Classification of Human Poses
Yoga-82: A New Dataset for Fine-grained Classification of Hu...
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ieee computer Society conference on computer vision and pattern recognition workshops (cvprw)
作者: Manisha Verma Sudhakar Kumawat Yuta Nakashima Shanmuganathan Raman Osaka University Japan Indian Institute of Technology Gandhinagar India
Human pose estimation is a well-known problem in computer vision to locate joint positions. Existing datasets for learning of poses are observed to be not challenging enough in terms of pose diversity, object occlusio... 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