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检索条件"机构=Institute of Computer Graphics and Vision Graz University of Technology"
861 条 记 录,以下是121-130 订阅
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Benchmarking Classical and Learning-Based Multibeam Point Cloud Registration
Benchmarking Classical and Learning-Based Multibeam Point Cl...
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IEEE International Conference on Robotics and Automation (ICRA)
作者: Li Ling Jun Zhang Nils Bore John Folkesson Anna Wåhlin Division of Robotics Perception and Learning (RPL) KTH Royal Institute of Technology Stockholm Sweden Institute of Computer Graphics and Vision (ICGV) TU Graz Austria Ocean Infinity Västra Frölunda Sweden Department of Marine Sciences University of Gothenburg Sweden
Deep learning has shown promising results for multiple 3D point cloud registration datasets. However, in the underwater domain, most registration of multibeam echo-sounder (MBES) point cloud data are still performed u... 详细信息
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One-sided Frank-Wolfe algorithms for saddle problems
arXiv
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arXiv 2021年
作者: Kolmogorov, Vladimir Pock, Thomas Institute of Science and Technology Austria Institute of Computer Graphics and Vision Graz University of Technology
We study a class of convex-concave saddle-point problems of the form minx maxy(Kx, y) + fP(x) - h∗(y) where K is a linear operator, fP is the sum of a convex function f with a Lipschitz-continuous gradient and the ind... 详细信息
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Removing fences from sweep motion videos using global 3D reconstruction and fence-aware light field rendering
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Computational Visual Media 2019年 第1期5卷 21-32页
作者: Chanya Lueangwattana Shohei Mori Hideo Saito Department of Science and Technology Keio University Institute of Computer Graphics and Vision Graz University of Technology
Diminishing the appearance of a fence in an image is a challenging research area due to the characteristics of fences(thinness, lack of texture, etc.) and the need for occluded background restoration. In this paper, w... 详细信息
来源: 评论
Weighting Attributes Based on the Greedy Algorithm Properties
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Procedia computer Science 2024年 246卷 4883-4892页
作者: Beata Zielosko Urszula Stańczyk Kamil Jabloński University of Silesia in Katowice Institute of Computer Science Bȩdzińska 39 41-200 Sosnowiec Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A 44-100 Gliwice Poland
Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim w... 详细信息
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MATE: Masked Autoencoders are Online 3D Test-Time Learners
arXiv
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arXiv 2022年
作者: Mirza, M. Jehanzeb Shin, Inkyu Lin, Wei Schriebl, Andreas Sun, Kunyang Choe, Jaesung Possegger, Horst Kozinski, Mateusz Kweon, In So Yoon, Kuk-Jin Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Christian Doppler Laboratory for Embedded Machine Learning Korea Republic of Southeast University China
Our MATE is the first Test-Time-Training (TTT) method designed for 3D data, which makes deep networks trained for point cloud classification robust to distribution shifts occurring in test data. Like existing TTT meth... 详细信息
来源: 评论
Mapillary Planet-Scale Depth Dataset  16th
Mapillary Planet-Scale Depth Dataset
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16th European Conference on computer vision, ECCV 2020
作者: Antequera, Manuel López Gargallo, Pau Hofinger, Markus Bulò, Samuel Rota Kuang, Yubin Kontschieder, Peter Facebook Menlo Park United States Institute of Computer Graphics and Vision Graz University of Technology Graz Austria
Learning-based methods produce remarkable results on single image depth tasks when trained on well-established benchmarks, however, there is a large gap from these benchmarks to real-world performance that is usually ... 详细信息
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CC-DCNet: Dynamic Convolutional Neural Network with Contrastive Constraints for Identifying Lung Cancer Subtypes on Multi-modality Images
arXiv
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arXiv 2024年
作者: Jin, Yuan Ma, Gege Chen, Geng Lyu, Tianling Egger, Jan Lyu, Junhui Zhang, Shaoting Zhu, Wentao Zhejiang Lab 311121 China Institute of Computer Graphics and Vision Graz University of Technology Graz8010 Austria School of Computer Science and Engineering Northwestern Polytechnical University Shaanxi Xi’an710072 China The Zhejiang University School of Medicine Sir Run Run Shaw Hospital Hangzhou310016 China Shanghai Artificial Intelligence Laboratory Shanghai200120 China
The accurate diagnosis of pathological subtypes of lung cancer is of paramount importance for follow-up treatments and prognosis managements. Assessment methods utilizing deep learning technologies have introduced nov... 详细信息
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Automatically Annotating Indoor Images with CAD Models via RGB-D Scans
arXiv
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arXiv 2022年
作者: Ainetter, Stefan Stekovic, Sinisa Fraundorfer, Friedrich Lepetit, Vincent Institute for Computer Graphics and Vision Graz University of Technology Graz Austria LIGM École des Ponts Univ Gustave Eiffel CNRS Marne-la-Vallée France
We present an automatic method for annotating images of indoor scenes with the CAD models of the objects by relying on RGB-D scans. Through a visual evaluation by 3D experts, we show that our method retrieves annotati... 详细信息
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MultiAR: A Multi-User Augmented Reality Platform for Biomedical Education
MultiAR: A Multi-User Augmented Reality Platform for Biomedi...
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
作者: Markus Perz Gijs Luijten Jens Kleesiek Dieter Schmalstieg Jan Egger Christina Gsaxner Institute of Computer Graphics and Vision Graz University of Technology Graz Austria Institute for Artificial Intelligence in Medicine University Medicine Essen Essen Germany Cancer Research Center Cologne Essen West German Cancer Center Essen Germany Institute for Visualization and Interactive Systems University of Stuttgart Stuttgart Germany Virtual and Extended Reality in Medicine (ZvRM) University Hospital Essen Essen Germany
This paper addresses the growing integration of Augmented Reality (AR) in biomedical sciences, emphasizing collaborative learning experiences. We present MultiAR, a versatile, domain-specific platform enabling multi-u... 详细信息
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Stochastic Modeling of Inhomogeneities in the Aortic Wall and Uncertainty Quantification using a Bayesian Encoder-Decoder Surrogate
arXiv
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arXiv 2022年
作者: Ranftl, Sascha Rolf-Pissarczyk, Malte Wolkerstorfer, Gloria Pepe, Antonio Egger, Jan von der Linden, Wolfgang Holzapfel, Gerhard A. Graz University of Technology Institute of Theoretical and Computational Physics Austria Graz Center for Computational Engineering Graz University of Technology Austria Graz University of Technology Institute of Biomechanics Austria Graz University of Technology Institute of Computer Graphics and Vision Austria University Medicine Essen Institute for AI in Medicine Essen Germany Department of Structural Analysis Trondheim Norway
Inhomogeneities in the aortic wall can lead to localized stress accumulations, possibly initiating dissection. In many cases, a dissection results from pathological changes such as fragmentation or loss of elastic fib... 详细信息
来源: 评论