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检索条件"机构=KAIST Robotics and Computer Vision Lab."
67 条 记 录,以下是11-20 订阅
排序:
A unified approach of multi-scale deep and hand-crafted features for defocus estimation
arXiv
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arXiv 2017年
作者: Park, Jinsun Tai, Yu-Wing Cho, Donghyeon Kweon, In So Robotics and Computer Vision Lab. KAIST Tencent YouTu Lab.
In this paper, we introduce robust and synergetic handcrafted features and a simple but efficient deep feature from a convolutional neural network (CNN) architecture for defocus estimation. This paper systematically a... 详细信息
来源: 评论
Globally optimal manhattan frame estimation in real-time
Globally optimal manhattan frame estimation in real-time
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2016 IEEE Conference on computer vision and Pattern Recognition, CVPR 2016
作者: Joo, Kyungdon Oh, Tae-Hyun Kim, Junsik Kweon, In So Robotics and Computer Vision Lab. KAIST Korea Republic of
Given a set of surface normals, we pose a Manhattan Frame (MF) estimation problem as a consensus set maximization that maximizes the number of inliers over the rotation search space. We solve this problem through a br... 详细信息
来源: 评论
VPGNet: Vanishing point guided network for lane and road marking detection and recognition
arXiv
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arXiv 2017年
作者: Lee, Seokju Kim, Junsik Yoon, Jae Shin Shin, Seunghak Bailo, Oleksandr Kim, Namil Lee, Tae-Hee Hong, Hyun Seok Han, Seung-Hoon Kweon, In So Robotics and Computer Vision Lab KAIST Samsung Electronics DMC R&D Center
In this paper, we propose a unified end-to-end trainable multi-task network that jointly handles lane and road marking detection and recognition that is guided by a vanishing point under adverse weather conditions. We... 详细信息
来源: 评论
Stereo matching with color and monochrome cameras in low-light conditions
Stereo matching with color and monochrome cameras in low-lig...
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2016 IEEE Conference on computer vision and Pattern Recognition, CVPR 2016
作者: Jeon, Hae-Gon Lee, Joon-Young Im, Sunghoon Ha, Hyowon Kweon, In So Robotics and Computer Vision Lab. KAIST Korea Republic of Adobe Research United States
Consumer devices with stereo cameras have become popular because of their low-cost depth sensing capability. However, those systems usually suffer from low imaging quality and inaccurate depth acquisition under low-li... 详细信息
来源: 评论
Why is the Winner the Best?
Why is the Winner the Best?
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Conference on computer vision and Pattern Recognition (CVPR)
作者: M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from t...
来源: 评论
Efficient 3D hand tracking in articulation subspaces for the manipulation of virtual objects  16
Efficient 3D hand tracking in articulation subspaces for the...
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33rd computer Graphics International Conference, CGI 2016
作者: Park, Gabyong Argyros, Antonis Woo, Woontack KAIST GSCT UVR Lab. Daejeon Korea Republic of Computational Vision and Robotics Lab. Institute of Computer Science FORTH University of Crete Greece
We propose an efficient method for model-based 3D tracking of hand articulations observed from an egocentric viewpoint that aims at supporting the manipulation of virtual objects. Previous modelbased approaches optimi... 详细信息
来源: 评论
Integrating mission, logistics, and task planning for skills-based robot control in industrial kitting applications  34
Integrating mission, logistics, and task planning for skills...
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34th Workshop of the UK Planning and Scheduling Special Interest Group, PlanSIG 2016
作者: Crosby, Matthew Petrick, Ronald P. A. Toscano, César Dias, Rui Correia Rovida, Francesco Krüger, Volker Department of Computer Science Heriot-Watt University EdinburghEH14 4AS United Kingdom INESC TEC Technology and Science Porto4200 - 465 Portugal Robotics Vision and Machine Intelligence Lab. Aalborg University Copenhagen2450 Denmark
This paper presents an integrated cognitive robotics system for industrial kitting operations in a modern factory setting. The robot system combines low-level robot control and execution monitoring with automated miss... 详细信息
来源: 评论
Globally Optimal Manhattan Frame Estimation in Real-time
Globally Optimal Manhattan Frame Estimation in Real-time
收藏 引用
IEEE Conference on computer vision and Pattern Recognition
作者: Kyungdon Joo Tae-Hyun Oh Junsik Kim In So Kweon Robotics and Computer Vision Lab. KAIST
Given a set of surface normals, we pose a Manhattan Frame (MF) estimation problem as a consensus set maximization that maximizes the number of inliers over the rotation search space. We solve this problem through a br... 详细信息
来源: 评论
Stereo Matching with Color and Monochrome Cameras in Low-light Conditions
Stereo Matching with Color and Monochrome Cameras in Low-lig...
收藏 引用
IEEE Conference on computer vision and Pattern Recognition
作者: Hae-Gon Jeon Joon-Young Lee Sunghoon Im Hyowon Ha In So Kweon Robotics and Computer Vision Lab. KAIST Adobe Research
Consumer devices with stereo cameras have become popular because of their low-cost depth sensing capability. However, those systems usually suffer from low imaging quality and inaccurate depth acquisition under low-li... 详细信息
来源: 评论
Accurate Camera Calibration Robust to Defocus using a Smartphone
Accurate Camera Calibration Robust to Defocus using a Smartp...
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IEEE International Conference on computer vision
作者: Hyowon Ha Yunsu Bok Kyungdon Joo Jiyoung Jung In So Kweon Robotics and Computer Vision Lab. KAIST
We propose a novel camera calibration method for defocused images using a smartphone under the assumption that the defocus blur is modeled as a convolution of a sharp image with a Gaussian point spread function (PSF).... 详细信息
来源: 评论