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| [1] | József Molnár, Dmitry Chetverikov, Quadratic Transformation for Planar Mapping of Implicit Surfaces, In Journal of Mathematical Imaging and Vision, volume 48, no. 1, pp. 176-184, 2014.
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| [2] | József Molnár, Dmitry Chetverikov, Delia Cabrera DeBuc, Wei Gao, Gábor Márk Somfai, Layer extraction in rodent retinal images acquired by optical coherence tomography, In Machine Vision and Applications, volume 23, no. 6, pp. 1129-1139, 2012.
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| [3] | József Molnár, Dmitry Chetverikov, Sándor Fazekas, Illumination-robust variational optical flow using cross-correlation, In Computer Vision and Image Understanding, volume 114, no. 10, pp. 1104-1114, 2010.
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| [1] | Attila Tanács, András Majdik, József Molnár, Atul Rai, Zoltan Kato, Establishing Correspondences between Planar Image Patches, In Proceedings of International Conference on Digital Image Computing: Techniques and Applications, Wollongong, New South Wales, Australia, pp. 1-7, 2014, IEEE. (Best Paper Award)
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| [2] | Attila Tanács, András Majdik, Levente Hajder, József Molnár, Zsolt Sánta, Zoltan Kato, Collaborative Mobile 3D Reconstruction of Urban Scenes, In Proceedings of ACCV Workshop on Intelligent Mobile and Egocentric Vision (C. V. Jawahar, Shiguang Shan, eds.), volume 9010 of Lecture Notes in Computer Science, Singapore, pp. 486-501, 2014, Springer.
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| [3] | József Molnár, Robert Frohlich, Dmitry Chetverikov, Zoltan Kato, 3D Reconstruction of Planar Patches Seen by Omnidirectional Cameras, In Proceedings of International Conference on Digital Image Computing: Techniques and Applications, Wollongong, Australia, pp. 1-8, 2014, IEEE.
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| [4] | József Molnár, Rui Huang, Zoltan Kato, 3D Reconstruction of Planar Surface Patches: A Direct Solution, In Proceedings of ACCV Workshop on Big Data in 3D Computer Vision (C. V. Jawahar, Shiguang Shan, eds.), volume 9008 of Lecture Notes in Computer Science, Singapore, pp. 286-300, 2014, Springer.
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| [5] | Dmitry Chetverikov, József Molnár, An Experimental Study of Image Components and Data Metrics for Illumination-Robust Variational Optical Flow, In Proceedings of International Conference on Pattern Recognition, pp. 1694-1697, 2010.
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