Image Restoration using Plug-and-Play CNN MAP Denoisers Article Swipe
Siavash Arjomand Bigdeli
,
David Honzátko
,
Sabine Süsstrunk
,
L. A. Dunbar
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.5220/0008990700850092
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.5220/0008990700850092
Plug-and-play denoisers can be used to perform generic image restoration tasks independent of the degradation type. These methods build on the fact that the Maximum a Posteriori (MAP) optimization can be solved using smaller sub-problems, including a MAP denoising optimization. We present the first end-to-end approach to MAP estimation for image denoising using deep neural networks. We show that our method is guaranteed to minimize the MAP denoising objective, which is then used in an optimization algorithm for generic image restoration. We provide theoretical analysis of our approach and show the quantitative performance of our method in several experiments. Our experimental results show that the proposed method can achieve 70x faster performance compared to the state-of-the-art, while maintaining the theoretical perspective of MAP.
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.5220/0008990700850092
- OA Status
- green
- Cited By
- 1
- References
- 22
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2995880605
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2995880605Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5220/0008990700850092Digital Object Identifier
- Title
-
Image Restoration using Plug-and-Play CNN MAP DenoisersWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Siavash Arjomand Bigdeli, David Honzátko, Sabine Süsstrunk, L. A. DunbarList of authors in order
- Landing page
-
https://doi.org/10.5220/0008990700850092Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1912.09299Direct OA link when available
- Concepts
-
Maximum a posteriori estimation, Image restoration, Computer science, Noise reduction, Artificial intelligence, Image (mathematics), Depth map, A priori and a posteriori, Perspective (graphical), Computer vision, Algorithm, Image processing, Mathematics, Maximum likelihood, Statistics, Philosophy, EpistemologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2020: 1Per-year citation counts (last 5 years)
- References (count)
-
22Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2995880605 |
|---|---|
| doi | https://doi.org/10.5220/0008990700850092 |
| ids.doi | https://doi.org/10.5220/0008990700850092 |
| ids.mag | 2995880605 |
| ids.openalex | https://openalex.org/W2995880605 |
| fwci | 0.10496732 |
| type | preprint |
| title | Image Restoration using Plug-and-Play CNN MAP Denoisers |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 92 |
| biblio.first_page | 85 |
| topics[0].id | https://openalex.org/T10688 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1707 |
| topics[0].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[0].display_name | Image and Signal Denoising Methods |
| topics[1].id | https://openalex.org/T10500 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9998000264167786 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2206 |
| topics[1].subfield.display_name | Computational Mechanics |
| topics[1].display_name | Sparse and Compressive Sensing Techniques |
| topics[2].id | https://openalex.org/T11105 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9995999932289124 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1707 |
| topics[2].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[2].display_name | Advanced Image Processing Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C9810830 |
| concepts[0].level | 3 |
| concepts[0].score | 0.866055965423584 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q635384 |
| concepts[0].display_name | Maximum a posteriori estimation |
| concepts[1].id | https://openalex.org/C106430172 |
| concepts[1].level | 4 |
| concepts[1].score | 0.7755696773529053 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q6002272 |
| concepts[1].display_name | Image restoration |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7540990710258484 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C163294075 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6334275007247925 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q581861 |
| concepts[3].display_name | Noise reduction |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.5331394672393799 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C115961682 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5305054187774658 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[5].display_name | Image (mathematics) |
| concepts[6].id | https://openalex.org/C141268832 |
| concepts[6].level | 3 |
| concepts[6].score | 0.48600372672080994 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q2940499 |
| concepts[6].display_name | Depth map |
| concepts[7].id | https://openalex.org/C75553542 |
| concepts[7].level | 2 |
| concepts[7].score | 0.46146920323371887 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q178161 |
| concepts[7].display_name | A priori and a posteriori |
| concepts[8].id | https://openalex.org/C12713177 |
| concepts[8].level | 2 |
| concepts[8].score | 0.43332892656326294 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q1900281 |
| concepts[8].display_name | Perspective (graphical) |
| concepts[9].id | https://openalex.org/C31972630 |
| concepts[9].level | 1 |
| concepts[9].score | 0.39489465951919556 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[9].display_name | Computer vision |
| concepts[10].id | https://openalex.org/C11413529 |
| concepts[10].level | 1 |
| concepts[10].score | 0.34202492237091064 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[10].display_name | Algorithm |
| concepts[11].id | https://openalex.org/C9417928 |
| concepts[11].level | 3 |
| concepts[11].score | 0.2662065625190735 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1070689 |
| concepts[11].display_name | Image processing |
| concepts[12].id | https://openalex.org/C33923547 |
| concepts[12].level | 0 |
| concepts[12].score | 0.13839271664619446 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[12].display_name | Mathematics |
| concepts[13].id | https://openalex.org/C49781872 |
| concepts[13].level | 2 |
| concepts[13].score | 0.11048442125320435 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q1045555 |
| concepts[13].display_name | Maximum likelihood |
| concepts[14].id | https://openalex.org/C105795698 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[14].display_name | Statistics |
| concepts[15].id | https://openalex.org/C138885662 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[15].display_name | Philosophy |
| concepts[16].id | https://openalex.org/C111472728 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q9471 |
| concepts[16].display_name | Epistemology |
| keywords[0].id | https://openalex.org/keywords/maximum-a-posteriori-estimation |
| keywords[0].score | 0.866055965423584 |
| keywords[0].display_name | Maximum a posteriori estimation |
| keywords[1].id | https://openalex.org/keywords/image-restoration |
| keywords[1].score | 0.7755696773529053 |
| keywords[1].display_name | Image restoration |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.7540990710258484 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/noise-reduction |
| keywords[3].score | 0.6334275007247925 |
| keywords[3].display_name | Noise reduction |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.5331394672393799 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/image |
| keywords[5].score | 0.5305054187774658 |
| keywords[5].display_name | Image (mathematics) |
| keywords[6].id | https://openalex.org/keywords/depth-map |
| keywords[6].score | 0.48600372672080994 |
| keywords[6].display_name | Depth map |
| keywords[7].id | https://openalex.org/keywords/a-priori-and-a-posteriori |
| keywords[7].score | 0.46146920323371887 |
| keywords[7].display_name | A priori and a posteriori |
| keywords[8].id | https://openalex.org/keywords/perspective |
| keywords[8].score | 0.43332892656326294 |
| keywords[8].display_name | Perspective (graphical) |
| keywords[9].id | https://openalex.org/keywords/computer-vision |
| keywords[9].score | 0.39489465951919556 |
| keywords[9].display_name | Computer vision |
| keywords[10].id | https://openalex.org/keywords/algorithm |
| keywords[10].score | 0.34202492237091064 |
| keywords[10].display_name | Algorithm |
| keywords[11].id | https://openalex.org/keywords/image-processing |
| keywords[11].score | 0.2662065625190735 |
| keywords[11].display_name | Image processing |
| keywords[12].id | https://openalex.org/keywords/mathematics |
| keywords[12].score | 0.13839271664619446 |
| keywords[12].display_name | Mathematics |
| keywords[13].id | https://openalex.org/keywords/maximum-likelihood |
| keywords[13].score | 0.11048442125320435 |
| keywords[13].display_name | Maximum likelihood |
| language | en |
| locations[0].id | doi:10.5220/0008990700850092 |
| locations[0].is_oa | False |
| locations[0].source | |
| locations[0].license | |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | proceedings-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
| locations[0].landing_page_url | https://doi.org/10.5220/0008990700850092 |
| locations[1].id | pmh:oai:arXiv.org:1912.09299 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | |
| locations[1].pdf_url | https://arxiv.org/pdf/1912.09299 |
| locations[1].version | submittedVersion |
| locations[1].raw_type | text |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | http://arxiv.org/abs/1912.09299 |
| locations[2].id | mag:2995880605 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306400194 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | True |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | arXiv (Cornell University) |
| locations[2].source.host_organization | https://openalex.org/I205783295 |
| locations[2].source.host_organization_name | Cornell University |
| locations[2].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[2].license | |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | |
| locations[2].license_id | |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | arXiv (Cornell University) |
| locations[2].landing_page_url | https://arxiv.org/pdf/1912.09299 |
| locations[3].id | pmh:oai:infoscience.epfl.ch:281096 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S4306400487 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | True |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | Infoscience (Ecole Polytechnique Fédérale de Lausanne) |
| locations[3].source.host_organization | |
| locations[3].source.host_organization_name | |
| locations[3].license | cc-by-nc-nd |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | conference proceedings |
| locations[3].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | |
| locations[3].landing_page_url | http://infoscience.epfl.ch/record/281096 |
| locations[4].id | doi:10.48550/arxiv.1912.09299 |
| locations[4].is_oa | True |
| locations[4].source.id | https://openalex.org/S4306400194 |
| locations[4].source.issn | |
| locations[4].source.type | repository |
| locations[4].source.is_oa | True |
| locations[4].source.issn_l | |
| locations[4].source.is_core | False |
| locations[4].source.is_in_doaj | False |
| locations[4].source.display_name | arXiv (Cornell University) |
| locations[4].source.host_organization | https://openalex.org/I205783295 |
| locations[4].source.host_organization_name | Cornell University |
| locations[4].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[4].license | |
| locations[4].pdf_url | |
| locations[4].version | |
| locations[4].raw_type | article |
| locations[4].license_id | |
| locations[4].is_accepted | False |
| locations[4].is_published | |
| locations[4].raw_source_name | |
| locations[4].landing_page_url | https://doi.org/10.48550/arxiv.1912.09299 |
| indexed_in | arxiv, crossref, datacite |
| authorships[0].author.id | https://openalex.org/A5024315163 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-2569-6473 |
| authorships[0].author.display_name | Siavash Arjomand Bigdeli |
| authorships[0].countries | CH |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I135218257 |
| authorships[0].affiliations[0].raw_affiliation_string | Centre Suisse d’Electronique et de Microtechnique (CSEM), Neuchâtel, Switzerland, --- Select a Country --- |
| authorships[0].institutions[0].id | https://openalex.org/I135218257 |
| authorships[0].institutions[0].ror | https://ror.org/05nrrsx06 |
| authorships[0].institutions[0].type | company |
| authorships[0].institutions[0].lineage | https://openalex.org/I135218257 |
| authorships[0].institutions[0].country_code | CH |
| authorships[0].institutions[0].display_name | Swiss Center for Electronics and Microtechnology (Switzerland) |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Siavash Bigdeli |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Centre Suisse d’Electronique et de Microtechnique (CSEM), Neuchâtel, Switzerland, --- Select a Country --- |
| authorships[1].author.id | https://openalex.org/A5087632602 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-3733-0356 |
| authorships[1].author.display_name | David Honzátko |
| authorships[1].countries | CH |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I135218257 |
| authorships[1].affiliations[0].raw_affiliation_string | Centre Suisse d’Electronique et de Microtechnique (CSEM), Neuchâtel, Switzerland, --- Select a Country --- |
| authorships[1].institutions[0].id | https://openalex.org/I135218257 |
| authorships[1].institutions[0].ror | https://ror.org/05nrrsx06 |
| authorships[1].institutions[0].type | company |
| authorships[1].institutions[0].lineage | https://openalex.org/I135218257 |
| authorships[1].institutions[0].country_code | CH |
| authorships[1].institutions[0].display_name | Swiss Center for Electronics and Microtechnology (Switzerland) |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | David Honzátko |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Centre Suisse d’Electronique et de Microtechnique (CSEM), Neuchâtel, Switzerland, --- Select a Country --- |
| authorships[2].author.id | https://openalex.org/A5078201467 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-0441-6068 |
| authorships[2].author.display_name | Sabine Süsstrunk |
| authorships[2].countries | CH |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I5124864 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, --- Select a Country --- |
| authorships[2].institutions[0].id | https://openalex.org/I5124864 |
| authorships[2].institutions[0].ror | https://ror.org/02s376052 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I2799323385, https://openalex.org/I5124864 |
| authorships[2].institutions[0].country_code | CH |
| authorships[2].institutions[0].display_name | École Polytechnique Fédérale de Lausanne |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sabine Süsstrunk |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, --- Select a Country --- |
| authorships[3].author.id | https://openalex.org/A5118899624 |
| authorships[3].author.orcid | https://orcid.org/0009-0000-3379-6170 |
| authorships[3].author.display_name | L. A. Dunbar |
| authorships[3].countries | CH |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I135218257 |
| authorships[3].affiliations[0].raw_affiliation_string | Centre Suisse d’Electronique et de Microtechnique (CSEM), Neuchâtel, Switzerland, --- Select a Country --- |
| authorships[3].institutions[0].id | https://openalex.org/I135218257 |
| authorships[3].institutions[0].ror | https://ror.org/05nrrsx06 |
| authorships[3].institutions[0].type | company |
| authorships[3].institutions[0].lineage | https://openalex.org/I135218257 |
| authorships[3].institutions[0].country_code | CH |
| authorships[3].institutions[0].display_name | Swiss Center for Electronics and Microtechnology (Switzerland) |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | L. Andrea Dunbar |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Centre Suisse d’Electronique et de Microtechnique (CSEM), Neuchâtel, Switzerland, --- Select a Country --- |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/1912.09299 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Image Restoration using Plug-and-Play CNN MAP Denoisers |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10688 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1707 |
| primary_topic.subfield.display_name | Computer Vision and Pattern Recognition |
| primary_topic.display_name | Image and Signal Denoising Methods |
| related_works | https://openalex.org/W3011678450, https://openalex.org/W2894090523, https://openalex.org/W2380341959, https://openalex.org/W2890076472, https://openalex.org/W2765915786, https://openalex.org/W3158399033, https://openalex.org/W3128141137, https://openalex.org/W2798427787, https://openalex.org/W3154660690, https://openalex.org/W3102148777, https://openalex.org/W2967023393, https://openalex.org/W2967502735, https://openalex.org/W3045407755, https://openalex.org/W3045472838, https://openalex.org/W3186516154, https://openalex.org/W3167568784, https://openalex.org/W2902402285, https://openalex.org/W2928817239, https://openalex.org/W2924693173, https://openalex.org/W3003592200 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2020 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 5 |
| best_oa_location.id | pmh:oai:arXiv.org:1912.09299 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/1912.09299 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/1912.09299 |
| primary_location.id | doi:10.5220/0008990700850092 |
| primary_location.is_oa | False |
| primary_location.source | |
| primary_location.license | |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | proceedings-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
| primary_location.landing_page_url | https://doi.org/10.5220/0008990700850092 |
| publication_date | 2020-01-01 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W2741183886, https://openalex.org/W2950788055, https://openalex.org/W2805167149, https://openalex.org/W2963073614, https://openalex.org/W1906770428, https://openalex.org/W2963391718, https://openalex.org/W2021347102, https://openalex.org/W2172275395, https://openalex.org/W2963299521, https://openalex.org/W2087416986, https://openalex.org/W2147298660, https://openalex.org/W3137695714, https://openalex.org/W2032506791, https://openalex.org/W2753778655, https://openalex.org/W2613155248, https://openalex.org/W2130975789, https://openalex.org/W2924128390, https://openalex.org/W2508457857, https://openalex.org/W2964013315, https://openalex.org/W2121927366, https://openalex.org/W2057480797, https://openalex.org/W2950560720 |
| referenced_works_count | 22 |
| abstract_inverted_index.a | 25, 36 |
| abstract_inverted_index.We | 40, 56, 81 |
| abstract_inverted_index.an | 74 |
| abstract_inverted_index.be | 3, 30 |
| abstract_inverted_index.in | 73, 96 |
| abstract_inverted_index.is | 61, 70 |
| abstract_inverted_index.of | 12, 85, 93, 121 |
| abstract_inverted_index.on | 19 |
| abstract_inverted_index.to | 5, 46, 63, 113 |
| abstract_inverted_index.70x | 109 |
| abstract_inverted_index.MAP | 37, 47, 66 |
| abstract_inverted_index.Our | 99 |
| abstract_inverted_index.and | 88 |
| abstract_inverted_index.can | 2, 29, 107 |
| abstract_inverted_index.for | 49, 77 |
| abstract_inverted_index.our | 59, 86, 94 |
| abstract_inverted_index.the | 13, 20, 23, 42, 65, 90, 104, 114, 118 |
| abstract_inverted_index.MAP. | 122 |
| abstract_inverted_index.deep | 53 |
| abstract_inverted_index.fact | 21 |
| abstract_inverted_index.show | 57, 89, 102 |
| abstract_inverted_index.that | 22, 58, 103 |
| abstract_inverted_index.then | 71 |
| abstract_inverted_index.used | 4, 72 |
| abstract_inverted_index.(MAP) | 27 |
| abstract_inverted_index.These | 16 |
| abstract_inverted_index.build | 18 |
| abstract_inverted_index.first | 43 |
| abstract_inverted_index.image | 8, 50, 79 |
| abstract_inverted_index.tasks | 10 |
| abstract_inverted_index.type. | 15 |
| abstract_inverted_index.using | 32, 52 |
| abstract_inverted_index.which | 69 |
| abstract_inverted_index.while | 116 |
| abstract_inverted_index.faster | 110 |
| abstract_inverted_index.method | 60, 95, 106 |
| abstract_inverted_index.neural | 54 |
| abstract_inverted_index.solved | 31 |
| abstract_inverted_index.Maximum | 24 |
| abstract_inverted_index.achieve | 108 |
| abstract_inverted_index.generic | 7, 78 |
| abstract_inverted_index.methods | 17 |
| abstract_inverted_index.perform | 6 |
| abstract_inverted_index.present | 41 |
| abstract_inverted_index.provide | 82 |
| abstract_inverted_index.results | 101 |
| abstract_inverted_index.several | 97 |
| abstract_inverted_index.smaller | 33 |
| abstract_inverted_index.analysis | 84 |
| abstract_inverted_index.approach | 45, 87 |
| abstract_inverted_index.compared | 112 |
| abstract_inverted_index.minimize | 64 |
| abstract_inverted_index.proposed | 105 |
| abstract_inverted_index.algorithm | 76 |
| abstract_inverted_index.denoisers | 1 |
| abstract_inverted_index.denoising | 38, 51, 67 |
| abstract_inverted_index.including | 35 |
| abstract_inverted_index.networks. | 55 |
| abstract_inverted_index.Posteriori | 26 |
| abstract_inverted_index.end-to-end | 44 |
| abstract_inverted_index.estimation | 48 |
| abstract_inverted_index.guaranteed | 62 |
| abstract_inverted_index.objective, | 68 |
| abstract_inverted_index.degradation | 14 |
| abstract_inverted_index.independent | 11 |
| abstract_inverted_index.maintaining | 117 |
| abstract_inverted_index.performance | 92, 111 |
| abstract_inverted_index.perspective | 120 |
| abstract_inverted_index.restoration | 9 |
| abstract_inverted_index.theoretical | 83, 119 |
| abstract_inverted_index.experimental | 100 |
| abstract_inverted_index.experiments. | 98 |
| abstract_inverted_index.optimization | 28, 75 |
| abstract_inverted_index.quantitative | 91 |
| abstract_inverted_index.restoration. | 80 |
| abstract_inverted_index.Plug-and-play | 0 |
| abstract_inverted_index.optimization. | 39 |
| abstract_inverted_index.sub-problems, | 34 |
| abstract_inverted_index.state-of-the-art, | 115 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.5899999737739563 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.37156433 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |