A brief analysis of the dense extreme inception network for edge detection
This work describes DexiNed, a Dense Extreme Inception Network for Edge Detection proposed by Xavier Soria, Edgar Riba and Angel Sappa in [IEEE Winter Conference on Applications of Computer Vision (WACV), 2020]. The network is organized in blocks that extract edges at different resolutions, which ar...
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| Format: | article |
| Idioma: | anglès |
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2022
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| Accés en línia: | https://www.ipol.im/pub/art/2022/423/ https://hdl.handle.net/20.500.12008/34134 |
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| _version_ | 1868890017134280704 |
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| author | Grompone von Gioi, Rafael |
| author2 | Randall, Gregory |
| author2_role | author |
| author_browse | Grompone von Gioi, Rafael Randall, Gregory |
| author_facet | Grompone von Gioi, Rafael Randall, Gregory |
| author_role | author |
| collection | COLIBRI |
| dc.contributor.none.fl_str_mv | Grompone von Gioi Rafael, Université Paris-Saclay, France Randall Gregory, Universidad de la República (Uruguay). Facultad de Ingeniería. |
| dc.creator.none.fl_str_mv | Grompone von Gioi, Rafael Randall, Gregory |
| dc.date.none.fl_str_mv | 2022-10-13T12:25:16Z 2022-10-13T12:25:16Z 2022 |
| dc.format.none.fl_str_mv | 15 p. application/pdf |
| dc.identifier.none.fl_str_mv | Grompone von Gioi, R y Randall, G. "A brief analysis of the dense extreme inception network for edge detection". IPOL. Journal Image Processing On Line. [en línea]. 2022, no 12, pp. 389-403. DOI: 10.5201/ipol.2022.423 2105–1232 https://www.ipol.im/pub/art/2022/423/ https://hdl.handle.net/20.500.12008/34134 10.5201/ipol.2022.423 |
| dc.language.none.fl_str_mv | en eng |
| dc.publisher.none.fl_str_mv | Centre Borelli, ENS Paris-Saclay; DMI, Universitat de les Illes Balears; Fing, Universidad de la República. |
| dc.relation.none.fl_str_mv | IPOL. Journal Image Processing On Line, no 12, Oct 2022, pp. 389-403. |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess Licencia Creative Commons Atribución - No Comercial - Compartir Igual (CC - By-NC-SA 4.0) |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.none.fl_str_mv | Image edge detection Neural network HED Xception |
| dc.title.none.fl_str_mv | A brief analysis of the dense extreme inception network for edge detection |
| dc.type.none.fl_str_mv | Artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | This work describes DexiNed, a Dense Extreme Inception Network for Edge Detection proposed by Xavier Soria, Edgar Riba and Angel Sappa in [IEEE Winter Conference on Applications of Computer Vision (WACV), 2020]. The network is organized in blocks that extract edges at different resolutions, which are then merged to produce a multiscale edge map. For training, the authors introduced an annotated dataset (BIPED) specifically designed for edge detection. We perform a brief analysis of the results produced by DexiNed, highlighting its quality but also indicating its limitations. Overall, DexiNed produces state-of-the-art results. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | anni_3f2d8d64f83c59d301ed8cf6fc01acaa |
| identifier_str_mv | Grompone von Gioi, R y Randall, G. "A brief analysis of the dense extreme inception network for edge detection". IPOL. Journal Image Processing On Line. [en línea]. 2022, no 12, pp. 389-403. DOI: 10.5201/ipol.2022.423 2105–1232 10.5201/ipol.2022.423 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en |
| network_acronym_str | anni |
| network_name_str | oai-lr-anni |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/34134 |
| publishDate | 2022 |
| publishDateSort | 2022 |
| publisher.none.fl_str_mv | Centre Borelli, ENS Paris-Saclay; DMI, Universitat de les Illes Balears; Fing, Universidad de la República. |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | Licencia Creative Commons Atribución - No Comercial - Compartir Igual (CC - By-NC-SA 4.0) |
| spelling | A brief analysis of the dense extreme inception network for edge detectionGrompone von Gioi, RafaelRandall, GregoryImage edge detectionNeural networkHEDXceptionThis work describes DexiNed, a Dense Extreme Inception Network for Edge Detection proposed by Xavier Soria, Edgar Riba and Angel Sappa in [IEEE Winter Conference on Applications of Computer Vision (WACV), 2020]. The network is organized in blocks that extract edges at different resolutions, which are then merged to produce a multiscale edge map. For training, the authors introduced an annotated dataset (BIPED) specifically designed for edge detection. We perform a brief analysis of the results produced by DexiNed, highlighting its quality but also indicating its limitations. Overall, DexiNed produces state-of-the-art results.Centre Borelli, ENS Paris-Saclay; DMI, Universitat de les Illes Balears; Fing, Universidad de la República.Grompone von Gioi Rafael, Université Paris-Saclay, FranceRandall Gregory, Universidad de la República (Uruguay). Facultad de Ingeniería.2022-10-13T12:25:16Z2022-10-13T12:25:16Z2022Artículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion15 p.application/pdfGrompone von Gioi, R y Randall, G. "A brief analysis of the dense extreme inception network for edge detection". IPOL. Journal Image Processing On Line. [en línea]. 2022, no 12, pp. 389-403. DOI: 10.5201/ipol.2022.4232105–1232https://www.ipol.im/pub/art/2022/423/https://hdl.handle.net/20.500.12008/3413410.5201/ipol.2022.423reponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaenengIPOL. Journal Image Processing On Line, no 12, Oct 2022, pp. 389-403.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución - No Comercial - Compartir Igual (CC - By-NC-SA 4.0)oai:colibri.udelar.edu.uy:20.500.12008/341342026-04-14T10:15:22Z |
| spellingShingle | A brief analysis of the dense extreme inception network for edge detection Grompone von Gioi, Rafael Image edge detection Neural network HED Xception |
| status_str | publishedVersion |
| title | A brief analysis of the dense extreme inception network for edge detection |
| title_full | A brief analysis of the dense extreme inception network for edge detection |
| title_fullStr | A brief analysis of the dense extreme inception network for edge detection |
| title_full_unstemmed | A brief analysis of the dense extreme inception network for edge detection |
| title_short | A brief analysis of the dense extreme inception network for edge detection |
| title_sort | A brief analysis of the dense extreme inception network for edge detection |
| topic | Image edge detection Neural network HED Xception |
| url | https://www.ipol.im/pub/art/2022/423/ https://hdl.handle.net/20.500.12008/34134 |