Image Cropping under Design Constraints Article Swipe
Takumi Nishiyasu
,
Wataru Shimoda
,
Yoichi Sato
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1145/3595916.3626412
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1145/3595916.3626412
Image cropping is essential in image editing for obtaining a compositionally\nenhanced image. In display media, image cropping is a prospective technique for\nautomatically creating media content. However, image cropping for media\ncontents is often required to satisfy various constraints, such as an aspect\nratio and blank regions for placing texts or objects. We call this problem\nimage cropping under design constraints. To achieve image cropping under design\nconstraints, we propose a score function-based approach, which computes scores\nfor cropped results whether aesthetically plausible and satisfies design\nconstraints. We explore two derived approaches, a proposal-based approach, and\na heatmap-based approach, and we construct a dataset for evaluating the\nperformance of the proposed approaches on image cropping under design\nconstraints. In experiments, we demonstrate that the proposed approaches\noutperform a baseline, and we observe that the proposal-based approach is\nbetter than the heatmap-based approach under the same computation cost, but the\nheatmap-based approach leads to better scores by increasing computation cost.\nThe experimental results indicate that balancing aesthetically plausible\nregions and satisfying design constraints is not a trivial problem and requires\nsensitive balance, and both proposed approaches are reasonable alternatives.\n
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1145/3595916.3626412
- https://dl.acm.org/doi/pdf/10.1145/3595916.3626412
- OA Status
- gold
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387687191
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4387687191Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1145/3595916.3626412Digital Object Identifier
- Title
-
Image Cropping under Design ConstraintsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-12-06Full publication date if available
- Authors
-
Takumi Nishiyasu, Wataru Shimoda, Yoichi SatoList of authors in order
- Landing page
-
https://doi.org/10.1145/3595916.3626412Publisher landing page
- PDF URL
-
https://dl.acm.org/doi/pdf/10.1145/3595916.3626412Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://dl.acm.org/doi/pdf/10.1145/3595916.3626412Direct OA link when available
- Concepts
-
Cropping, Computer science, Computation, Image (mathematics), Construct (python library), Baseline (sea), Artificial intelligence, Computer vision, Mathematical optimization, Algorithm, Mathematics, Programming language, Biology, Oceanography, Agriculture, Ecology, GeologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4387687191 |
|---|---|
| doi | https://doi.org/10.1145/3595916.3626412 |
| ids.doi | https://doi.org/10.1145/3595916.3626412 |
| ids.openalex | https://openalex.org/W4387687191 |
| fwci | 0.0 |
| type | preprint |
| title | Image Cropping under Design Constraints |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 7 |
| biblio.first_page | 1 |
| topics[0].id | https://openalex.org/T11605 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9995999932289124 |
| 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 | Visual Attention and Saliency Detection |
| topics[1].id | https://openalex.org/T11019 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9980000257492065 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1707 |
| topics[1].subfield.display_name | Computer Vision and Pattern Recognition |
| topics[1].display_name | Image Enhancement Techniques |
| topics[2].id | https://openalex.org/T10627 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9973000288009644 |
| 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 and Video Retrieval Techniques |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C13558536 |
| concepts[0].level | 3 |
| concepts[0].score | 0.8973008394241333 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q785116 |
| concepts[0].display_name | Cropping |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.7351101040840149 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C45374587 |
| concepts[2].level | 2 |
| concepts[2].score | 0.7344280481338501 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q12525525 |
| concepts[2].display_name | Computation |
| concepts[3].id | https://openalex.org/C115961682 |
| concepts[3].level | 2 |
| concepts[3].score | 0.7173747420310974 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q860623 |
| concepts[3].display_name | Image (mathematics) |
| concepts[4].id | https://openalex.org/C2780801425 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5008416175842285 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q5164392 |
| concepts[4].display_name | Construct (python library) |
| concepts[5].id | https://openalex.org/C12725497 |
| concepts[5].level | 2 |
| concepts[5].score | 0.48762574791908264 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q810247 |
| concepts[5].display_name | Baseline (sea) |
| concepts[6].id | https://openalex.org/C154945302 |
| concepts[6].level | 1 |
| concepts[6].score | 0.3915506601333618 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[6].display_name | Artificial intelligence |
| concepts[7].id | https://openalex.org/C31972630 |
| concepts[7].level | 1 |
| concepts[7].score | 0.32682472467422485 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[7].display_name | Computer vision |
| concepts[8].id | https://openalex.org/C126255220 |
| concepts[8].level | 1 |
| concepts[8].score | 0.32257306575775146 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q141495 |
| concepts[8].display_name | Mathematical optimization |
| concepts[9].id | https://openalex.org/C11413529 |
| concepts[9].level | 1 |
| concepts[9].score | 0.2791672945022583 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[9].display_name | Algorithm |
| concepts[10].id | https://openalex.org/C33923547 |
| concepts[10].level | 0 |
| concepts[10].score | 0.1876012682914734 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[10].display_name | Mathematics |
| concepts[11].id | https://openalex.org/C199360897 |
| concepts[11].level | 1 |
| concepts[11].score | 0.060011059045791626 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[11].display_name | Programming language |
| concepts[12].id | https://openalex.org/C86803240 |
| concepts[12].level | 0 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[12].display_name | Biology |
| concepts[13].id | https://openalex.org/C111368507 |
| concepts[13].level | 1 |
| concepts[13].score | 0.0 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q43518 |
| concepts[13].display_name | Oceanography |
| concepts[14].id | https://openalex.org/C118518473 |
| concepts[14].level | 2 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11451 |
| concepts[14].display_name | Agriculture |
| concepts[15].id | https://openalex.org/C18903297 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q7150 |
| concepts[15].display_name | Ecology |
| concepts[16].id | https://openalex.org/C127313418 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[16].display_name | Geology |
| keywords[0].id | https://openalex.org/keywords/cropping |
| keywords[0].score | 0.8973008394241333 |
| keywords[0].display_name | Cropping |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.7351101040840149 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/computation |
| keywords[2].score | 0.7344280481338501 |
| keywords[2].display_name | Computation |
| keywords[3].id | https://openalex.org/keywords/image |
| keywords[3].score | 0.7173747420310974 |
| keywords[3].display_name | Image (mathematics) |
| keywords[4].id | https://openalex.org/keywords/construct |
| keywords[4].score | 0.5008416175842285 |
| keywords[4].display_name | Construct (python library) |
| keywords[5].id | https://openalex.org/keywords/baseline |
| keywords[5].score | 0.48762574791908264 |
| keywords[5].display_name | Baseline (sea) |
| keywords[6].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[6].score | 0.3915506601333618 |
| keywords[6].display_name | Artificial intelligence |
| keywords[7].id | https://openalex.org/keywords/computer-vision |
| keywords[7].score | 0.32682472467422485 |
| keywords[7].display_name | Computer vision |
| keywords[8].id | https://openalex.org/keywords/mathematical-optimization |
| keywords[8].score | 0.32257306575775146 |
| keywords[8].display_name | Mathematical optimization |
| keywords[9].id | https://openalex.org/keywords/algorithm |
| keywords[9].score | 0.2791672945022583 |
| keywords[9].display_name | Algorithm |
| keywords[10].id | https://openalex.org/keywords/mathematics |
| keywords[10].score | 0.1876012682914734 |
| keywords[10].display_name | Mathematics |
| keywords[11].id | https://openalex.org/keywords/programming-language |
| keywords[11].score | 0.060011059045791626 |
| keywords[11].display_name | Programming language |
| language | en |
| locations[0].id | doi:10.1145/3595916.3626412 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | |
| locations[0].pdf_url | https://dl.acm.org/doi/pdf/10.1145/3595916.3626412 |
| 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 | ACM Multimedia Asia 2023 |
| locations[0].landing_page_url | https://doi.org/10.1145/3595916.3626412 |
| locations[1].id | pmh:oai:arXiv.org:2310.08892 |
| 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/2310.08892 |
| 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/2310.08892 |
| indexed_in | arxiv, crossref |
| authorships[0].author.id | https://openalex.org/A5035981523 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-8464-7500 |
| authorships[0].author.display_name | Takumi Nishiyasu |
| authorships[0].countries | JP |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210109338 |
| authorships[0].affiliations[0].raw_affiliation_string | The University of Tokyo, JP |
| authorships[0].institutions[0].id | https://openalex.org/I4210109338 |
| authorships[0].institutions[0].ror | https://ror.org/022cvpj02 |
| authorships[0].institutions[0].type | healthcare |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210109338 |
| authorships[0].institutions[0].country_code | JP |
| authorships[0].institutions[0].display_name | University of Tokyo Hospital |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Takumi Nishiyasu |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | The University of Tokyo, JP |
| authorships[1].author.id | https://openalex.org/A5051127663 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6238-9697 |
| authorships[1].author.display_name | Wataru Shimoda |
| authorships[1].countries | JP |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210089607 |
| authorships[1].affiliations[0].raw_affiliation_string | CyberAgent.Inc, JP |
| authorships[1].institutions[0].id | https://openalex.org/I4210089607 |
| authorships[1].institutions[0].ror | https://ror.org/0060jg679 |
| authorships[1].institutions[0].type | company |
| authorships[1].institutions[0].lineage | https://openalex.org/I4210089607 |
| authorships[1].institutions[0].country_code | JP |
| authorships[1].institutions[0].display_name | CyberAgent (Japan) |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Wataru Shimoda |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | CyberAgent.Inc, JP |
| authorships[2].author.id | https://openalex.org/A5045996641 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0097-4537 |
| authorships[2].author.display_name | Yoichi Sato |
| authorships[2].countries | JP |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I4210109338 |
| authorships[2].affiliations[0].raw_affiliation_string | The University of Tokyo, JP |
| authorships[2].institutions[0].id | https://openalex.org/I4210109338 |
| authorships[2].institutions[0].ror | https://ror.org/022cvpj02 |
| authorships[2].institutions[0].type | healthcare |
| authorships[2].institutions[0].lineage | https://openalex.org/I4210109338 |
| authorships[2].institutions[0].country_code | JP |
| authorships[2].institutions[0].display_name | University of Tokyo Hospital |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Yoichi Sato |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | The University of Tokyo, JP |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://dl.acm.org/doi/pdf/10.1145/3595916.3626412 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Image Cropping under Design Constraints |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11605 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9995999932289124 |
| 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 | Visual Attention and Saliency Detection |
| related_works | https://openalex.org/W2366107444, https://openalex.org/W2383111961, https://openalex.org/W2365952365, https://openalex.org/W4388145910, https://openalex.org/W2352448290, https://openalex.org/W2380820513, https://openalex.org/W2381570729, https://openalex.org/W1976205134, https://openalex.org/W2913146933, https://openalex.org/W4248336175 |
| cited_by_count | 0 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1145/3595916.3626412 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://dl.acm.org/doi/pdf/10.1145/3595916.3626412 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | proceedings-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | ACM Multimedia Asia 2023 |
| best_oa_location.landing_page_url | https://doi.org/10.1145/3595916.3626412 |
| primary_location.id | doi:10.1145/3595916.3626412 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | |
| primary_location.pdf_url | https://dl.acm.org/doi/pdf/10.1145/3595916.3626412 |
| 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 | ACM Multimedia Asia 2023 |
| primary_location.landing_page_url | https://doi.org/10.1145/3595916.3626412 |
| publication_date | 2023-12-06 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2949676527, https://openalex.org/W1851029461, https://openalex.org/W2896805562, https://openalex.org/W2575939610, https://openalex.org/W2586372171, https://openalex.org/W2023081159, https://openalex.org/W2580110234, https://openalex.org/W2082335776, https://openalex.org/W3186050100, https://openalex.org/W4206070552, https://openalex.org/W2198929403, https://openalex.org/W4312598291, https://openalex.org/W2622328527, https://openalex.org/W2775725209, https://openalex.org/W2944041622, https://openalex.org/W3034818671, https://openalex.org/W4224281996, https://openalex.org/W2107363596, https://openalex.org/W2078807908, https://openalex.org/W2069639113, https://openalex.org/W2007773296, https://openalex.org/W2013339738, https://openalex.org/W3202461321, https://openalex.org/W2100618994, https://openalex.org/W2060502770, https://openalex.org/W2963312801, https://openalex.org/W2804743778, https://openalex.org/W2798986039, https://openalex.org/W2963010685, https://openalex.org/W2973725754, https://openalex.org/W4312549256, https://openalex.org/W4200514690, https://openalex.org/W3087104340, https://openalex.org/W1522301498, https://openalex.org/W1686810756, https://openalex.org/W4390190485, https://openalex.org/W2962897394 |
| referenced_works_count | 37 |
| abstract_inverted_index.a | 9, 18, 65, 85, 94, 116, 159 |
| abstract_inverted_index.In | 12, 108 |
| abstract_inverted_index.To | 57 |
| abstract_inverted_index.We | 49, 80 |
| abstract_inverted_index.an | 39 |
| abstract_inverted_index.as | 38 |
| abstract_inverted_index.by | 142 |
| abstract_inverted_index.in | 4 |
| abstract_inverted_index.is | 2, 17, 30, 157 |
| abstract_inverted_index.of | 99 |
| abstract_inverted_index.on | 103 |
| abstract_inverted_index.or | 47 |
| abstract_inverted_index.to | 33, 139 |
| abstract_inverted_index.we | 63, 92, 110, 119 |
| abstract_inverted_index.and | 41, 77, 91, 118, 153, 162, 165 |
| abstract_inverted_index.are | 169 |
| abstract_inverted_index.but | 135 |
| abstract_inverted_index.for | 7, 28, 44, 96 |
| abstract_inverted_index.not | 158 |
| abstract_inverted_index.the | 100, 113, 122, 127, 131 |
| abstract_inverted_index.two | 82 |
| abstract_inverted_index.both | 166 |
| abstract_inverted_index.call | 50 |
| abstract_inverted_index.same | 132 |
| abstract_inverted_index.such | 37 |
| abstract_inverted_index.than | 126 |
| abstract_inverted_index.that | 112, 121, 149 |
| abstract_inverted_index.this | 51 |
| abstract_inverted_index.Image | 0 |
| abstract_inverted_index.blank | 42 |
| abstract_inverted_index.cost, | 134 |
| abstract_inverted_index.image | 5, 15, 26, 59, 104 |
| abstract_inverted_index.leads | 138 |
| abstract_inverted_index.media | 23 |
| abstract_inverted_index.often | 31 |
| abstract_inverted_index.score | 66 |
| abstract_inverted_index.texts | 46 |
| abstract_inverted_index.under | 54, 61, 106, 130 |
| abstract_inverted_index.which | 69 |
| abstract_inverted_index.and\na | 88 |
| abstract_inverted_index.better | 140 |
| abstract_inverted_index.design | 55, 155 |
| abstract_inverted_index.image. | 11 |
| abstract_inverted_index.media, | 14 |
| abstract_inverted_index.scores | 141 |
| abstract_inverted_index.achieve | 58 |
| abstract_inverted_index.cropped | 72 |
| abstract_inverted_index.dataset | 95 |
| abstract_inverted_index.derived | 83 |
| abstract_inverted_index.display | 13 |
| abstract_inverted_index.editing | 6 |
| abstract_inverted_index.explore | 81 |
| abstract_inverted_index.observe | 120 |
| abstract_inverted_index.placing | 45 |
| abstract_inverted_index.problem | 161 |
| abstract_inverted_index.propose | 64 |
| abstract_inverted_index.regions | 43 |
| abstract_inverted_index.results | 73, 147 |
| abstract_inverted_index.satisfy | 34 |
| abstract_inverted_index.trivial | 160 |
| abstract_inverted_index.various | 35 |
| abstract_inverted_index.whether | 74 |
| abstract_inverted_index.However, | 25 |
| abstract_inverted_index.approach | 124, 129, 137 |
| abstract_inverted_index.balance, | 164 |
| abstract_inverted_index.computes | 70 |
| abstract_inverted_index.content. | 24 |
| abstract_inverted_index.creating | 22 |
| abstract_inverted_index.cropping | 1, 16, 27, 53, 60, 105 |
| abstract_inverted_index.indicate | 148 |
| abstract_inverted_index.objects. | 48 |
| abstract_inverted_index.proposed | 101, 114, 167 |
| abstract_inverted_index.required | 32 |
| abstract_inverted_index.approach, | 68, 87, 90 |
| abstract_inverted_index.balancing | 150 |
| abstract_inverted_index.baseline, | 117 |
| abstract_inverted_index.construct | 93 |
| abstract_inverted_index.essential | 3 |
| abstract_inverted_index.obtaining | 8 |
| abstract_inverted_index.plausible | 76 |
| abstract_inverted_index.satisfies | 78 |
| abstract_inverted_index.technique | 20 |
| abstract_inverted_index.approaches | 102, 168 |
| abstract_inverted_index.cost.\nThe | 145 |
| abstract_inverted_index.evaluating | 97 |
| abstract_inverted_index.increasing | 143 |
| abstract_inverted_index.is\nbetter | 125 |
| abstract_inverted_index.reasonable | 170 |
| abstract_inverted_index.satisfying | 154 |
| abstract_inverted_index.approaches, | 84 |
| abstract_inverted_index.computation | 133, 144 |
| abstract_inverted_index.constraints | 156 |
| abstract_inverted_index.demonstrate | 111 |
| abstract_inverted_index.prospective | 19 |
| abstract_inverted_index.scores\nfor | 71 |
| abstract_inverted_index.constraints, | 36 |
| abstract_inverted_index.constraints. | 56 |
| abstract_inverted_index.experimental | 146 |
| abstract_inverted_index.experiments, | 109 |
| abstract_inverted_index.aesthetically | 75, 151 |
| abstract_inverted_index.aspect\nratio | 40 |
| abstract_inverted_index.heatmap-based | 89, 128 |
| abstract_inverted_index.function-based | 67 |
| abstract_inverted_index.problem\nimage | 52 |
| abstract_inverted_index.proposal-based | 86, 123 |
| abstract_inverted_index.alternatives.\n | 171 |
| abstract_inverted_index.media\ncontents | 29 |
| abstract_inverted_index.the\nperformance | 98 |
| abstract_inverted_index.for\nautomatically | 21 |
| abstract_inverted_index.plausible\nregions | 152 |
| abstract_inverted_index.the\nheatmap-based | 136 |
| abstract_inverted_index.requires\nsensitive | 163 |
| abstract_inverted_index.design\nconstraints, | 62 |
| abstract_inverted_index.design\nconstraints. | 79, 107 |
| abstract_inverted_index.approaches\noutperform | 115 |
| abstract_inverted_index.compositionally\nenhanced | 10 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.15410654 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |