Zobrazeno 1 - 10
of 62
pro vyhledávání: '"Fabio Ganovelli"'
Publikováno v:
Computational Visual Media, Vol 4, Iss 4, Pp 367-383 (2018)
Abstract We present a novel approach to automatically recover, from a small set of partially overlapping spherical images, an indoor structure representation in terms of a 3D floor plan registered with a set of 3D environment maps. We introduce sever
Externí odkaz:
https://doaj.org/article/d10553866d7442e5b5fc49633a75209a
Publikováno v:
Proceedings of the 9th International Conference on Geographical Information Systems Theory, Applications and Management.
Publikováno v:
Computer graphics forum
38 (2019): 347–358. doi:10.1111/cgf.13842
info:cnr-pdr/source/autori:Pintore G.; Ganovelli F.; Villanueva A.J.; Gobbetti E./titolo:Automatic modeling of cluttered multi-room floor plans from panoramic images/doi:10.1111%2Fcgf.13842/rivista:Computer graphics forum (Print)/anno:2019/pagina_da:347/pagina_a:358/intervallo_pagine:347–358/volume:38
38 (2019): 347–358. doi:10.1111/cgf.13842
info:cnr-pdr/source/autori:Pintore G.; Ganovelli F.; Villanueva A.J.; Gobbetti E./titolo:Automatic modeling of cluttered multi-room floor plans from panoramic images/doi:10.1111%2Fcgf.13842/rivista:Computer graphics forum (Print)/anno:2019/pagina_da:347/pagina_a:358/intervallo_pagine:347–358/volume:38
We present a novel and light-weight approach to capture and reconstruct structured 3D models of multi-room floor plans. Starting from a small set of registered panoramic images, we automatically generate a 3D layout of the rooms and of all the main o
Publikováno v:
Computational Visual Media, Vol 4, Iss 4, Pp 367-383 (2018)
Computational visual media (Beijing. Print) 4 (2018): 367–383. doi:10.1007/s41095-018-0125-9
info:cnr-pdr/source/autori:Pintore G.; Ganovelli F.; Pintus R.; Scopigno R.; Gobbetti E./titolo:3D floor plan recovery from overlapping spherical images/doi:10.1007%2Fs41095-018-0125-9/rivista:Computational visual media (Beijing. Print)/anno:2018/pagina_da:367/pagina_a:383/intervallo_pagine:367–383/volume:4
Computational visual media (Beijing. Print) 4 (2018): 367–383. doi:10.1007/s41095-018-0125-9
info:cnr-pdr/source/autori:Pintore G.; Ganovelli F.; Pintus R.; Scopigno R.; Gobbetti E./titolo:3D floor plan recovery from overlapping spherical images/doi:10.1007%2Fs41095-018-0125-9/rivista:Computational visual media (Beijing. Print)/anno:2018/pagina_da:367/pagina_a:383/intervallo_pagine:367–383/volume:4
We present a novel approach to automatically recover, from a small set of partially overlapping spherical images, an indoor structure representation in terms of a 3D floor plan registered with a set of 3D environment maps. % We introduce several impr
Autor:
Rui Gong, Massimiliano Corsini, Paolo Cignoni, Fabio Ganovelli, Francesco Banterle, Luc Van Gool
Publikováno v:
ICIP 2021-28th IEEE International Conference on Image Processing, pp. 3667–3671, Anchorage, Alaska, USA, 19-22/09/2021
2021 IEEE International Conference on Image Processing (ICIP)
2021 IEEE International Conference on Image Processing (ICIP)
Structure-from-Motion (SfM) using the frames of a video sequence can be a challenging task because there is a lot of redundant information, the computational time increases quadratically with the number of frames, there would be low-quality images (e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b12a8112cccddb0a3135e228159b3e48
https://openportal.isti.cnr.it/doc?id=people______::2b7eca0f653a8e8b96da91305d509bcf
https://openportal.isti.cnr.it/doc?id=people______::2b7eca0f653a8e8b96da91305d509bcf
Autor:
Lizeth Joseline Fuentes-Perez, Renato Pajarola, Enrico Gobbetti, Claudio Mura, Giovanni Pintore, Fabio Ganovelli
Publikováno v:
SIGGRAPH Courses
ACM SIGGRAPH 2020 Courses
SIGGRAPH '20-ACM SIGGRAPH 2020 Courses, Online Conference, August 24-28, 2020
info:cnr-pdr/source/autori:Pintore G.; Mura C.; Ganovelli F.; Fuentes-Perez L.; Pajarola R.; Gobbetti E./congresso_nome:SIGGRAPH '20-ACM SIGGRAPH 2020 Courses/congresso_luogo:Online Conference/congresso_data:August 24-28, 2020/anno:2020/pagina_da:/pagina_a:/intervallo_pagine
ACM SIGGRAPH 2020 Courses
SIGGRAPH '20-ACM SIGGRAPH 2020 Courses, Online Conference, August 24-28, 2020
info:cnr-pdr/source/autori:Pintore G.; Mura C.; Ganovelli F.; Fuentes-Perez L.; Pajarola R.; Gobbetti E./congresso_nome:SIGGRAPH '20-ACM SIGGRAPH 2020 Courses/congresso_luogo:Online Conference/congresso_data:August 24-28, 2020/anno:2020/pagina_da:/pagina_a:/intervallo_pagine
Tutorial notes Creating high-level structured 3D models of real-world indoor scenes from captured data is a fundamental task which has important applications in many fields. Given the complexity and variability of interior environments and the need t
Autor:
Claudio Mura, Enrico Gobbetti, Fabio Ganovelli, Lizeth Joseline Fuentes-Perez, Renato Pajarola, Giovanni Pintore
Publikováno v:
Computer Graphics Forum
Computer graphics forum
39 (2020): 667–699. doi:10.1111/cgf.14021
info:cnr-pdr/source/autori:Pintore G.; Mura C.; Ganovelli F.; Fuentes-Perez L.; Pajarola R.; Gobbetti E./titolo:State-of-the-art in Automatic 3D Reconstruction of Structured Indoor Environments/doi:10.1111%2Fcgf.14021/rivista:Computer graphics forum (Print)/anno:2020/pagina_da:667/pagina_a:699/intervallo_pagine:667–699/volume:39
Computer graphics forum
39 (2020): 667–699. doi:10.1111/cgf.14021
info:cnr-pdr/source/autori:Pintore G.; Mura C.; Ganovelli F.; Fuentes-Perez L.; Pajarola R.; Gobbetti E./titolo:State-of-the-art in Automatic 3D Reconstruction of Structured Indoor Environments/doi:10.1111%2Fcgf.14021/rivista:Computer graphics forum (Print)/anno:2020/pagina_da:667/pagina_a:699/intervallo_pagine:667–699/volume:39
Creating high-level structured 3D models of real-world indoor scenes from captured data is a fundamental task which has important applications in many fields. Given the complexity and variability of interior environments and the need to cope with noi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d144f418a2a920036099342ba952271f
https://dspace.crs4.it/jspui/handle/1138/12
https://dspace.crs4.it/jspui/handle/1138/12
Publikováno v:
IEEE computer graphics and applications 40 (2020): 140–147. doi:10.1109/MCG.2019.2958274
info:cnr-pdr/source/autori:Capece N.; Banterle F.; Cignoni P.; Ganovelli F.; Erra U.; Potel M./titolo:Turning a Smartphone Selfie into a Studio Portrait/doi:10.1109%2FMCG.2019.2958274/rivista:IEEE computer graphics and applications/anno:2020/pagina_da:140/pagina_a:147/intervallo_pagine:140–147/volume:40
info:cnr-pdr/source/autori:Capece N.; Banterle F.; Cignoni P.; Ganovelli F.; Erra U.; Potel M./titolo:Turning a Smartphone Selfie into a Studio Portrait/doi:10.1109%2FMCG.2019.2958274/rivista:IEEE computer graphics and applications/anno:2020/pagina_da:140/pagina_a:147/intervallo_pagine:140–147/volume:40
We introduce a novel algorithm that turns a flash selfie taken with a smartphone into a studio-like photograph with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in a controlled env
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cd889a6bda84fcae691b51fb218ca05
https://publications.cnr.it/doc/424580
https://publications.cnr.it/doc/424580
Autor:
Paolo Cignoni, Fabio Ganovelli, Ugo Erra, Nicola Capece, Roberto Scopigno, Francesco Banterle
Publikováno v:
Signal processing. Image communication 77 (2019): 28–39. doi:10.1016/j.image.2019.05.013
info:cnr-pdr/source/autori:Capece N.; Banterle F.; Cignoni P.; Ganovelli F.; Scopigno R.; Erra U./titolo:DeepFlash: turning a flash selfie into a studio portrait/doi:10.1016%2Fj.image.2019.05.013/rivista:Signal processing. Image communication/anno:2019/pagina_da:28/pagina_a:39/intervallo_pagine:28–39/volume:77
info:cnr-pdr/source/autori:Capece N.; Banterle F.; Cignoni P.; Ganovelli F.; Scopigno R.; Erra U./titolo:DeepFlash: turning a flash selfie into a studio portrait/doi:10.1016%2Fj.image.2019.05.013/rivista:Signal processing. Image communication/anno:2019/pagina_da:28/pagina_a:39/intervallo_pagine:28–39/volume:77
We present a method for turning a flash selfie taken with a smartphone into a photograph as if it was taken in a studio setting with uniform lighting. Our method uses a convolutional neural network trained on a set of pairs of photographs acquired in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d243f3354068335066db4900b13682cb
http://arxiv.org/abs/1901.04252
http://arxiv.org/abs/1901.04252
Publikováno v:
Computers & graphics 77 (2018): 16–29. doi:10.1016/j.cag.2018.09.013
info:cnr-pdr/source/autori:Pintore G.; Pintus R.; Ganovelli F.; Scopigno R.; Gobbetti E./titolo:Recovering 3D existing-conditions of indoor structures from spherical images/doi:10.1016%2Fj.cag.2018.09.013/rivista:Computers & graphics/anno:2018/pagina_da:16/pagina_a:29/intervallo_pagine:16–29/volume:77
info:cnr-pdr/source/autori:Pintore G.; Pintus R.; Ganovelli F.; Scopigno R.; Gobbetti E./titolo:Recovering 3D existing-conditions of indoor structures from spherical images/doi:10.1016%2Fj.cag.2018.09.013/rivista:Computers & graphics/anno:2018/pagina_da:16/pagina_a:29/intervallo_pagine:16–29/volume:77
We present a vision-based approach to automatically recover the 3D existing-conditions information of an indoor structure, starting from a small set of overlapping spherical images. The recovered 3D model includes the as-built 3D room layout with the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43a42718338d2da511575573e2e16b76
https://openportal.isti.cnr.it/doc?id=people______::bf1e6d5c1d31243fe2f30e68131530a3
https://openportal.isti.cnr.it/doc?id=people______::bf1e6d5c1d31243fe2f30e68131530a3