--- _id: '670' abstract: - lang: eng text: We propose an efficient method to model paper tearing in the context of interactive modeling. The method uses geometrical information to automatically detect potential starting points of tears. We further introduce a new hybrid geometrical and physical-based method to compute the trajectory of tears while procedurally synthesizing high resolution details of the tearing path using a texture based approach. The results obtained are compared with real paper and with previous studies on the expected geometric paths of paper that tears. article_processing_charge: No article_type: original author: - first_name: Camille full_name: Schreck, Camille id: 2B14B676-F248-11E8-B48F-1D18A9856A87 last_name: Schreck - first_name: Damien full_name: Rohmer, Damien last_name: Rohmer - first_name: Stefanie full_name: Hahmann, Stefanie last_name: Hahmann citation: ama: Schreck C, Rohmer D, Hahmann S. Interactive paper tearing. Computer Graphics Forum. 2017;36(2):95-106. doi:10.1111/cgf.13110 apa: Schreck, C., Rohmer, D., & Hahmann, S. (2017). Interactive paper tearing. Computer Graphics Forum. Wiley. https://doi.org/10.1111/cgf.13110 chicago: Schreck, Camille, Damien Rohmer, and Stefanie Hahmann. “Interactive Paper Tearing.” Computer Graphics Forum. Wiley, 2017. https://doi.org/10.1111/cgf.13110. ieee: C. Schreck, D. Rohmer, and S. Hahmann, “Interactive paper tearing,” Computer Graphics Forum, vol. 36, no. 2. Wiley, pp. 95–106, 2017. ista: Schreck C, Rohmer D, Hahmann S. 2017. Interactive paper tearing. Computer Graphics Forum. 36(2), 95–106. mla: Schreck, Camille, et al. “Interactive Paper Tearing.” Computer Graphics Forum, vol. 36, no. 2, Wiley, 2017, pp. 95–106, doi:10.1111/cgf.13110. short: C. Schreck, D. Rohmer, S. Hahmann, Computer Graphics Forum 36 (2017) 95–106. date_created: 2018-12-11T11:47:49Z date_published: 2017-05-01T00:00:00Z date_updated: 2021-01-12T08:08:37Z day: '01' ddc: - '000' department: - _id: ChWo doi: 10.1111/cgf.13110 intvolume: ' 36' issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://hal.inria.fr/hal-01647113/file/eg_2017_schreck_paper_tearing.pdf month: '05' oa: 1 oa_version: Published Version page: 95 - 106 project: - _id: 25357BD2-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 24352-N23 name: 'Deep Pictures: Creating Visual and Haptic Vector Images' publication: Computer Graphics Forum publication_identifier: issn: - '01677055' publication_status: published publisher: Wiley publist_id: '7056' quality_controlled: '1' scopus_import: 1 status: public title: Interactive paper tearing type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 36 year: '2017' ... --- _id: '1367' abstract: - lang: eng text: One of the major challenges in physically based modelling is making simulations efficient. Adaptive models provide an essential solution to these efficiency goals. These models are able to self-adapt in space and time, attempting to provide the best possible compromise between accuracy and speed. This survey reviews the adaptive solutions proposed so far in computer graphics. Models are classified according to the strategy they use for adaptation, from time-stepping and freezing techniques to geometric adaptivity in the form of structured grids, meshes and particles. Applications range from fluids, through deformable bodies, to articulated solids. acknowledgement: This work was partly supported by the starting grants ADAPT and BigSplash, as well as the advanced grant EXPRESSIVE from the European Research Council (ERC-2012-StG_20111012, ERC-2014-StG_638176 and ERC-2011-ADG_20110209). article_processing_charge: No author: - first_name: Pierre full_name: Manteaux, Pierre last_name: Manteaux - first_name: Christopher J full_name: Wojtan, Christopher J id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87 last_name: Wojtan orcid: 0000-0001-6646-5546 - first_name: Rahul full_name: Narain, Rahul last_name: Narain - first_name: Stéphane full_name: Redon, Stéphane last_name: Redon - first_name: François full_name: Faure, François last_name: Faure - first_name: Marie full_name: Cani, Marie last_name: Cani citation: ama: Manteaux P, Wojtan C, Narain R, Redon S, Faure F, Cani M. Adaptive physically based models in computer graphics. Computer Graphics Forum. 2017;36(6):312-337. doi:10.1111/cgf.12941 apa: Manteaux, P., Wojtan, C., Narain, R., Redon, S., Faure, F., & Cani, M. (2017). Adaptive physically based models in computer graphics. Computer Graphics Forum. Wiley-Blackwell. https://doi.org/10.1111/cgf.12941 chicago: Manteaux, Pierre, Chris Wojtan, Rahul Narain, Stéphane Redon, François Faure, and Marie Cani. “Adaptive Physically Based Models in Computer Graphics.” Computer Graphics Forum. Wiley-Blackwell, 2017. https://doi.org/10.1111/cgf.12941. ieee: P. Manteaux, C. Wojtan, R. Narain, S. Redon, F. Faure, and M. Cani, “Adaptive physically based models in computer graphics,” Computer Graphics Forum, vol. 36, no. 6. Wiley-Blackwell, pp. 312–337, 2017. ista: Manteaux P, Wojtan C, Narain R, Redon S, Faure F, Cani M. 2017. Adaptive physically based models in computer graphics. Computer Graphics Forum. 36(6), 312–337. mla: Manteaux, Pierre, et al. “Adaptive Physically Based Models in Computer Graphics.” Computer Graphics Forum, vol. 36, no. 6, Wiley-Blackwell, 2017, pp. 312–37, doi:10.1111/cgf.12941. short: P. Manteaux, C. Wojtan, R. Narain, S. Redon, F. Faure, M. Cani, Computer Graphics Forum 36 (2017) 312–337. date_created: 2018-12-11T11:51:37Z date_published: 2017-09-01T00:00:00Z date_updated: 2023-09-20T11:05:36Z day: '01' ddc: - '000' department: - _id: ChWo doi: 10.1111/cgf.12941 external_id: isi: - '000408634200019' file: - access_level: open_access checksum: 7676e9a9ead6d58c3000988c97deb2ef content_type: application/pdf creator: system date_created: 2018-12-12T10:16:21Z date_updated: 2020-07-14T12:44:47Z file_id: '5208' file_name: IST-2016-634-v1+1_starAdaptivity-cgf.pdf file_size: 1434439 relation: main_file file_date_updated: 2020-07-14T12:44:47Z has_accepted_license: '1' intvolume: ' 36' isi: 1 issue: '6' language: - iso: eng month: '09' oa: 1 oa_version: Submitted Version page: 312 - 337 publication: Computer Graphics Forum publication_identifier: issn: - '01677055' publication_status: published publisher: Wiley-Blackwell publist_id: '5873' pubrep_id: '634' quality_controlled: '1' scopus_import: '1' status: public title: Adaptive physically based models in computer graphics type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 36 year: '2017' ... --- _id: '1152' abstract: - lang: eng text: We propose a new memetic strategy that can solve the multi-physics, complex inverse problems, formulated as the multi-objective optimization ones, in which objectives are misfits between the measured and simulated states of various governing processes. The multi-deme structure of the strategy allows for both, intensive, relatively cheap exploration with a moderate accuracy and more accurate search many regions of Pareto set in parallel. The special type of selection operator prefers the coherent alternative solutions, eliminating artifacts appearing in the particular processes. The additional accuracy increment is obtained by the parallel convex searches applied to the local scalarizations of the misfit vector. The strategy is dedicated for solving ill-conditioned problems, for which inverting the single physical process can lead to the ambiguous results. The skill of the selection in artifact elimination is shown on the benchmark problem, while the whole strategy was applied for identification of oil deposits, where the misfits are related to various frequencies of the magnetic and electric waves of the magnetotelluric measurements. 2016 Elsevier B.V. article_processing_charge: No author: - first_name: Ewa P full_name: Gajda-Zagorska, Ewa P id: 47794CF0-F248-11E8-B48F-1D18A9856A87 last_name: Gajda-Zagorska - first_name: Robert full_name: Schaefer, Robert last_name: Schaefer - first_name: Maciej full_name: Smołka, Maciej last_name: Smołka - first_name: David full_name: Pardo, David last_name: Pardo - first_name: Julen full_name: Alvarez Aramberri, Julen last_name: Alvarez Aramberri citation: ama: Gajda-Zagorska EP, Schaefer R, Smołka M, Pardo D, Alvarez Aramberri J. A multi objective memetic inverse solver reinforced by local optimization methods. Journal of Computational Science. 2017;18:85-94. doi:10.1016/j.jocs.2016.06.007 apa: Gajda-Zagorska, E. P., Schaefer, R., Smołka, M., Pardo, D., & Alvarez Aramberri, J. (2017). A multi objective memetic inverse solver reinforced by local optimization methods. Journal of Computational Science. Elsevier. https://doi.org/10.1016/j.jocs.2016.06.007 chicago: Gajda-Zagorska, Ewa P, Robert Schaefer, Maciej Smołka, David Pardo, and Julen Alvarez Aramberri. “A Multi Objective Memetic Inverse Solver Reinforced by Local Optimization Methods.” Journal of Computational Science. Elsevier, 2017. https://doi.org/10.1016/j.jocs.2016.06.007. ieee: E. P. Gajda-Zagorska, R. Schaefer, M. Smołka, D. Pardo, and J. Alvarez Aramberri, “A multi objective memetic inverse solver reinforced by local optimization methods,” Journal of Computational Science, vol. 18. Elsevier, pp. 85–94, 2017. ista: Gajda-Zagorska EP, Schaefer R, Smołka M, Pardo D, Alvarez Aramberri J. 2017. A multi objective memetic inverse solver reinforced by local optimization methods. Journal of Computational Science. 18, 85–94. mla: Gajda-Zagorska, Ewa P., et al. “A Multi Objective Memetic Inverse Solver Reinforced by Local Optimization Methods.” Journal of Computational Science, vol. 18, Elsevier, 2017, pp. 85–94, doi:10.1016/j.jocs.2016.06.007. short: E.P. Gajda-Zagorska, R. Schaefer, M. Smołka, D. Pardo, J. Alvarez Aramberri, Journal of Computational Science 18 (2017) 85–94. date_created: 2018-12-11T11:50:26Z date_published: 2017-01-01T00:00:00Z date_updated: 2023-09-20T11:29:44Z day: '01' ddc: - '000' department: - _id: ChWo doi: 10.1016/j.jocs.2016.06.007 external_id: isi: - '000393528700009' file: - access_level: open_access content_type: application/pdf creator: dernst date_created: 2019-01-18T08:43:16Z date_updated: 2019-01-18T08:43:16Z file_id: '5842' file_name: 2016_jocs_ewa.pdf file_size: 1083911 relation: main_file success: 1 file_date_updated: 2019-01-18T08:43:16Z has_accepted_license: '1' intvolume: ' 18' isi: 1 language: - iso: eng month: '01' oa: 1 oa_version: Submitted Version page: 85 - 94 publication: Journal of Computational Science publication_identifier: issn: - '18777503' publication_status: published publisher: Elsevier publist_id: '6206' quality_controlled: '1' scopus_import: '1' status: public title: A multi objective memetic inverse solver reinforced by local optimization methods type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 18 year: '2017' ... --- _id: '998' abstract: - lang: eng text: 'A major open problem on the road to artificial intelligence is the development of incrementally learning systems that learn about more and more concepts over time from a stream of data. In this work, we introduce a new training strategy, iCaRL, that allows learning in such a class-incremental way: only the training data for a small number of classes has to be present at the same time and new classes can be added progressively. iCaRL learns strong classifiers and a data representation simultaneously. This distinguishes it from earlier works that were fundamentally limited to fixed data representations and therefore incompatible with deep learning architectures. We show by experiments on CIFAR-100 and ImageNet ILSVRC 2012 data that iCaRL can learn many classes incrementally over a long period of time where other strategies quickly fail. ' article_processing_charge: No author: - first_name: Sylvestre Alvise full_name: Rebuffi, Sylvestre Alvise last_name: Rebuffi - first_name: Alexander full_name: Kolesnikov, Alexander id: 2D157DB6-F248-11E8-B48F-1D18A9856A87 last_name: Kolesnikov - first_name: Georg full_name: Sperl, Georg id: 4DD40360-F248-11E8-B48F-1D18A9856A87 last_name: Sperl - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 citation: ama: 'Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587' apa: 'Rebuffi, S. A., Kolesnikov, A., Sperl, G., & Lampert, C. (2017). iCaRL: Incremental classifier and representation learning (Vol. 2017, pp. 5533–5542). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.587' chicago: 'Rebuffi, Sylvestre Alvise, Alexander Kolesnikov, Georg Sperl, and Christoph Lampert. “ICaRL: Incremental Classifier and Representation Learning,” 2017:5533–42. IEEE, 2017. https://doi.org/10.1109/CVPR.2017.587.' ieee: 'S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.' ista: 'Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. 2017. iCaRL: Incremental classifier and representation learning. CVPR: Computer Vision and Pattern Recognition vol. 2017, 5533–5542.' mla: 'Rebuffi, Sylvestre Alvise, et al. ICaRL: Incremental Classifier and Representation Learning. Vol. 2017, IEEE, 2017, pp. 5533–42, doi:10.1109/CVPR.2017.587.' short: S.A. Rebuffi, A. Kolesnikov, G. Sperl, C. Lampert, in:, IEEE, 2017, pp. 5533–5542. conference: end_date: 2017-07-26 location: Honolulu, HA, United States name: 'CVPR: Computer Vision and Pattern Recognition' start_date: 2017-07-21 date_created: 2018-12-11T11:49:37Z date_published: 2017-04-14T00:00:00Z date_updated: 2023-09-22T09:51:58Z day: '14' department: - _id: ChLa - _id: ChWo doi: 10.1109/CVPR.2017.587 ec_funded: 1 external_id: isi: - '000418371405066' intvolume: ' 2017' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1611.07725 month: '04' oa: 1 oa_version: Submitted Version page: 5533 - 5542 project: - _id: 2532554C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '308036' name: Lifelong Learning of Visual Scene Understanding publication_identifier: isbn: - 978-153860457-1 publication_status: published publisher: IEEE publist_id: '6400' quality_controlled: '1' scopus_import: '1' status: public title: 'iCaRL: Incremental classifier and representation learning' type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 2017 year: '2017' ... --- _id: '839' abstract: - lang: eng text: 'This thesis describes a brittle fracture simulation method for visual effects applications. Building upon a symmetric Galerkin boundary element method, we first compute stress intensity factors following the theory of linear elastic fracture mechanics. We then use these stress intensities to simulate the motion of a propagating crack front at a significantly higher resolution than the overall deformation of the breaking object. Allowing for spatial variations of the material''s toughness during crack propagation produces visually realistic, highly-detailed fracture surfaces. Furthermore, we introduce approximations for stress intensities and crack opening displacements, resulting in both practical speed-up and theoretically superior runtime complexity compared to previous methods. While we choose a quasi-static approach to fracture mechanics, ignoring dynamic deformations, we also couple our fracture simulation framework to a standard rigid-body dynamics solver, enabling visual effects artists to simulate both large scale motion, as well as fracturing due to collision forces in a combined system. As fractures inside of an object grow, their geometry must be represented both in the coarse boundary element mesh, as well as at the desired fine output resolution. Using a boundary element method, we avoid complicated volumetric meshing operations. Instead we describe a simple set of surface meshing operations that allow us to progressively add cracks to the mesh of an object and still re-use all previously computed entries of the linear boundary element system matrix. On the high resolution level, we opt for an implicit surface representation. We then describe how to capture fracture surfaces during crack propagation, as well as separate the individual fragments resulting from the fracture process, based on this implicit representation. We show results obtained with our method, either solving the full boundary element system in every time step, or alternatively using our fast approximations. These results demonstrate that both of these methods perform well in basic test cases and produce realistic fracture surfaces. Furthermore we show that our fast approximations substantially out-perform the standard approach in more demanding scenarios. Finally, these two methods naturally combine, using the full solution while the problem size is manageably small and switching to the fast approximations later on. The resulting hybrid method gives the user a direct way to choose between speed and accuracy of the simulation. ' acknowledgement: "ERC H2020 programme (grant agreement no. 638176)\r\nFirst of all, let me thank my committee members, especially my supervisor, Chris\r\nWojtan, for supporting me throughout my PhD. Obviously, none of this work would\r\nhave been possible without you.\r\nFurthermore, Thank You to all the people who have contributed to this work in various\r\nways, in particular Martin Schanz and his group for providing and supporting the\r\nHyENA boundary element library, as well as Eder Miguel and Morten Bojsen-Hansen\r\nfor (repeatedly) proof reading and providing valuable suggestions during the writing\r\nof this thesis.\r\nI would also like to thank Bernd Bickel, and all the members – past and present – of his\r\nand Chris’ research groups at IST Austria for always providing honest and insightful\r\nfeedback throughout many joint group meetings, as well as Christopher Batty, Eitan\r\nGrinspun, and Fang Da for many insights into boundary element methods during our\r\ncollaboration.\r\nAs only virtual objects have been harmed in the process of creating this work, I would\r\nlike to acknowledge the Stanford scanning repository for providing the “Bunny” and\r\n“Armadillo” models, the AIM@SHAPE repository for “Pierre’s hand, watertight”, and\r\nS. Gainsbourg for the “Column” via Archive3D.net. Sorry for breaking these models\r\nin many different ways.\r\n" alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: David full_name: Hahn, David id: 357A6A66-F248-11E8-B48F-1D18A9856A87 last_name: Hahn citation: ama: Hahn D. Brittle fracture simulation with boundary elements for computer graphics. 2017. doi:10.15479/AT:ISTA:th_855 apa: Hahn, D. (2017). Brittle fracture simulation with boundary elements for computer graphics. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_855 chicago: Hahn, David. “Brittle Fracture Simulation with Boundary Elements for Computer Graphics.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_855. ieee: D. Hahn, “Brittle fracture simulation with boundary elements for computer graphics,” Institute of Science and Technology Austria, 2017. ista: Hahn D. 2017. Brittle fracture simulation with boundary elements for computer graphics. Institute of Science and Technology Austria. mla: Hahn, David. Brittle Fracture Simulation with Boundary Elements for Computer Graphics. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_855. short: D. Hahn, Brittle Fracture Simulation with Boundary Elements for Computer Graphics, Institute of Science and Technology Austria, 2017. date_created: 2018-12-11T11:48:47Z date_published: 2017-08-14T00:00:00Z date_updated: 2024-02-21T13:48:02Z day: '14' ddc: - '004' - '005' - '006' - '531' - '621' degree_awarded: PhD department: - _id: ChWo doi: 10.15479/AT:ISTA:th_855 ec_funded: 1 file: - access_level: open_access checksum: 6c1ae8c90bfaba5e089417fefbc4a272 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:46Z date_updated: 2020-07-14T12:48:13Z file_id: '5100' file_name: IST-2017-855-v1+1_thesis_online_pdfA.pdf file_size: 14596191 relation: main_file - access_level: closed checksum: 421672f68d563b029869c5cf1713f919 content_type: application/zip creator: dernst date_created: 2019-04-05T08:40:30Z date_updated: 2020-07-14T12:48:13Z file_id: '6207' file_name: 2017_thesis_Hahn_source.zip file_size: 15060566 relation: source_file file_date_updated: 2020-07-14T12:48:13Z has_accepted_license: '1' language: - iso: eng license: https://creativecommons.org/licenses/by-sa/4.0/ month: '08' oa: 1 oa_version: Published Version page: '124' project: - _id: 2533E772-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '638176' name: Efficient Simulation of Natural Phenomena at Extremely Large Scales publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publist_id: '6809' pubrep_id: '855' related_material: record: - id: '1362' relation: part_of_dissertation status: public - id: '1633' relation: part_of_dissertation status: public - id: '5568' relation: popular_science status: public status: public supervisor: - first_name: Christopher J full_name: Wojtan, Christopher J id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87 last_name: Wojtan orcid: 0000-0001-6646-5546 title: Brittle fracture simulation with boundary elements for computer graphics tmp: image: /images/cc_by_sa.png legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) short: CC BY-SA (4.0) type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2017' ...