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检索条件"机构=Computer Vision and Robotics Laboratory"
644 条 记 录,以下是231-240 订阅
排序:
Learning to infer the depth map of a hand from its color image
arXiv
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arXiv 2018年
作者: Nicodemou, Vassilis C. Oikonomidis, Iason Tzimiropoulos, Georgios Argyros, Antonis Computational Vision and Robotics Laboratory Institute of Computer Science FORTH Greece Computer Science Department University of Crete Greece Computer Vision Laboratory University of Nottingham United Kingdom
We propose the first approach to the problem of inferring the depth map of a human hand based on a single RGB image. We achieve this with a Convolutional Neural Network (CNN) that employs a stacked hourglass model as ... 详细信息
来源: 评论
Robust road marking detection & recognition using density-based grouping & machine learning techniques  17
Robust road marking detection & recognition using density-ba...
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17th IEEE Winter Conference on Applications of computer vision, WACV 2017
作者: Bailo, Oleksandr Lee, Seokju Rameau, Francois Yoon, Jae Shin Kweon, In So KAIST Robotics and Computer Vision Laboratory United States
This paper presents a robust approach for road marking detection and recognition from images captured by an embedded camera mounted on a car. Our method is designed to cope with illumination changes, shadows, and hars... 详细信息
来源: 评论
Gaussian curvature filter on 3d mesh
arXiv
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arXiv 2020年
作者: Tang, Wenming Gong, Yuanhao Liu, Kanglin Liu, Jun Pan, Wei Liu, Bozhi Qiu, Guoping College of Information Engineering Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Mechanical & Automotive Engineering South China University of Technology Department of Research and Development OPT Machine Vision Tech Co. Ltd Jinsheng Road Changan Dongguan Guangdong523860 China School of Computer Science University of Nottingham NottinghamNG8 1BB United Kingdom
Minimizing Gaussian curvature of meshes is fundamentally important for obtaining smooth and developable surfaces. However, there is a lack of computationally efficient and robust Gaussian curvature optimization method... 详细信息
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A novel hybrid convolutional neural network for accurate organ segmentation in 3d head and neck CT images
arXiv
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arXiv 2021年
作者: Chen, Zijie Li, Cheng He, Junjun Ye, Jin Song, Diping Wang, Shanshan Gu, Lixu Qiao, Yu Shenzhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Shanghai AI Lab Shanghai China Shenzhen Yino Intelligence Techonology Co. Ltd. Guangdong Shenzhen China Co. Ltd. Guangdong Shenzhen China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Peng Cheng Laboratory Guangdong Shenzhen China Pazhou Lab Guangdong Guangzhou China
Radiation therapy (RT) is widely employed in the clinic for the treatment of head and neck (HaN) cancers. An essential step of RT planning is the accurate segmentation of various organs-at-risks (OARs) in HaN CT image... 详细信息
来源: 评论
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
arXiv
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arXiv 2024年
作者: Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St
Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to thei... 详细信息
来源: 评论
Vehicular Multi-Camera Sensor System for Automated Visual Inspection of Electric Power Distribution Equipment
Vehicular Multi-Camera Sensor System for Automated Visual In...
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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
作者: Jinsun Park Ukcheol Shin Gyumin Shim Kyungdon Joo Francois Rameau Junhyeok Kim Dong-Geol Choi In So Kweon Robotics and Computer Vision Laboratory School of Electrical Engineering KAIST Daejeon Republic of Korea Korea Electric Power Corporation Korea Electric Power Research Institute Daejeon Republic of Korea Department of Information and Communication Engineering Hanbat National University Daejeon Republic of Korea
In this paper, we present a multi-camera sensor system along with its control algorithm for automated visual inspection from a moving vehicle. To accomplish this task, we propose a unique hardware configuration consis...
来源: 评论
Fast Perception, Planning, and Execution for a Robotic Butler: Wheeled Humanoid M-Hubo
Fast Perception, Planning, and Execution for a Robotic Butle...
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2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
作者: Moonyoung Lee Yujin Heo Jinyong Park Hyun-Dae Yang Ho-Deok Jang Philipp Benz Hyunsub Park In So Kweon Jun-Ho Oh Research Center Korea Advanced Institute of Science and Technology 291 Daehak-ro Yuseong-gu Daejeon Korea Robotics and Computer Vision Laboratory that is in charge of object perception part Korea Advanced Institute of Science and Technology 291 Daehakro Yuseong-gu Daejeon Korea
As the aging population grows at a rapid rate, there is an ever growing need for service robot platforms that can provide daily assistance at practical speed with reliable performance. In order to assist with daily ta...
来源: 评论
Understanding Human Motion and Gestures for Underwater Human-Robot Collaboration
arXiv
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arXiv 2018年
作者: Islam, Md Jahidul Interactive Robotics and Vision Laboratory Department of Computer Science and Engineering University of Minnesota- Twin Cities United States
In this paper, we present a number of robust methodologies for an underwater robot to visually detect, follow, and interact with a diver for collaborative task execution. We design and develop two autonomous diver-fol... 详细信息
来源: 评论
Deep representation of industrial components using simulated images
Deep representation of industrial components using simulated...
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2017 IEEE International Conference on robotics and Automation, ICRA 2017
作者: Kim, Seong-Heum Choe, Gyeongmin Ahn, Byungtae Kweon, In So Robotics and Computer Vision Laboratory School of Electrical Engineering KAIST Daejeon Korea Republic of
In this paper, we present a visual learning framework to retrieve a 3D model and estimate its pose from a single image. To increase the quantity and quality of training data, we define our simulation space in the near... 详细信息
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Generative 3D hand tracking with spatially constrained pose sampling  28
Generative 3D hand tracking with spatially constrained pose ...
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28th British Machine vision Conference, BMVC 2017
作者: Roditakis, Konstantinos Makris, Alexandros Argyros, Antonis A. Computational Vision and Robotics Laboratory Institute of Computer Science FORTH Greece Computer Science Department University of Crete Greece
We present a method for 3D hand tracking that exploits spatial constraints in the form of end effector (fingertip) locations. The method follows a generative, hypothesize-and-test approach and uses a hierarchical part... 详细信息
来源: 评论