Privacy-Preserving V2X Collaborative Perception Integrating Unknown Collaborators Article Swipe
Bin Lü
,
Xinyu Xiao
,
Changzhou Zhang
,
Zhou Yang
,
Zhiyu Xiang
,
Hangguan Shan
,
Eryun Liu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i6.32619
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v39i6.32619
Vehicle-to-everything (V2X) collaborative perception has recently gained increasing attention in autonomous driving due to its ability to enhance scene understanding by integrating information from other collaborators, e.g. vehicles or infrastructure. Existing algorithms usually share deep features to achieve a trade-off between accuracy and bandwidth. However, most of these methods require joint training of all agents, which results in privacy leakage and is impractical and unacceptable in the real world. Sharing prediction results seems to be a direct solution, but its performance is suboptimal and sensitive to localization noise and communication delay. In this paper, we propose a privacy-preserving collaborative perception framework, where each agent is separately trained with its own dataset and the ego vehicle needs to integrate with completely unknown collaborators. Specifically, we propose MSD, a multi-scale feature fusion method combined with deformable attention, to better fuse features of different agents. We also propose a plug-in domain adapter to align the features from unknown collaborators to ego-domain. Extensive experiments on the challenging DAIR-V2X and V2V4Real demonstrate that: 1) MSD achieves remarkable performance, outperforming others by at least 2.8% and 6.7% in AP0.7 on DAIR-V2X and V2V4Real, respectively; 2) After domain adaptation, it significantly outperforms the No Fusion, Late Fusion scenarios and can approach or even surpass the performance of joint training. We truly achieves privacy-preserving collaboration, providing a new paradigm for the study of collaborative perception, which is crucial for practical applications.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v39i6.32619
- https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774
- OA Status
- diamond
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409366844
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4409366844Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1609/aaai.v39i6.32619Digital Object Identifier
- Title
-
Privacy-Preserving V2X Collaborative Perception Integrating Unknown CollaboratorsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-04-11Full publication date if available
- Authors
-
Bin Lü, Xinyu Xiao, Changzhou Zhang, Zhou Yang, Zhiyu Xiang, Hangguan Shan, Eryun LiuList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v39i6.32619Publisher landing page
- PDF URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774Direct OA link when available
- Concepts
-
Perception, Computer science, Internet privacy, Human–computer interaction, Computer security, Psychology, NeuroscienceTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4409366844 |
|---|---|
| doi | https://doi.org/10.1609/aaai.v39i6.32619 |
| ids.doi | https://doi.org/10.1609/aaai.v39i6.32619 |
| ids.openalex | https://openalex.org/W4409366844 |
| fwci | 0.0 |
| type | article |
| title | Privacy-Preserving V2X Collaborative Perception Integrating Unknown Collaborators |
| biblio.issue | 6 |
| biblio.volume | 39 |
| biblio.last_page | 5810 |
| biblio.first_page | 5802 |
| topics[0].id | https://openalex.org/T10764 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9837999939918518 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Privacy-Preserving Technologies in Data |
| topics[1].id | https://openalex.org/T13382 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9833999872207642 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2207 |
| topics[1].subfield.display_name | Control and Systems Engineering |
| topics[1].display_name | Robotics and Automated Systems |
| topics[2].id | https://openalex.org/T10273 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9729999899864197 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1705 |
| topics[2].subfield.display_name | Computer Networks and Communications |
| topics[2].display_name | IoT and Edge/Fog Computing |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C26760741 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6303045153617859 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q160402 |
| concepts[0].display_name | Perception |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.5624694228172302 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C108827166 |
| concepts[2].level | 1 |
| concepts[2].score | 0.5403952598571777 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q175975 |
| concepts[2].display_name | Internet privacy |
| concepts[3].id | https://openalex.org/C107457646 |
| concepts[3].level | 1 |
| concepts[3].score | 0.39100348949432373 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q207434 |
| concepts[3].display_name | Human–computer interaction |
| concepts[4].id | https://openalex.org/C38652104 |
| concepts[4].level | 1 |
| concepts[4].score | 0.36478883028030396 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q3510521 |
| concepts[4].display_name | Computer security |
| concepts[5].id | https://openalex.org/C15744967 |
| concepts[5].level | 0 |
| concepts[5].score | 0.2907178997993469 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[5].display_name | Psychology |
| concepts[6].id | https://openalex.org/C169760540 |
| concepts[6].level | 1 |
| concepts[6].score | 0.06161549687385559 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q207011 |
| concepts[6].display_name | Neuroscience |
| keywords[0].id | https://openalex.org/keywords/perception |
| keywords[0].score | 0.6303045153617859 |
| keywords[0].display_name | Perception |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.5624694228172302 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/internet-privacy |
| keywords[2].score | 0.5403952598571777 |
| keywords[2].display_name | Internet privacy |
| keywords[3].id | https://openalex.org/keywords/human–computer-interaction |
| keywords[3].score | 0.39100348949432373 |
| keywords[3].display_name | Human–computer interaction |
| keywords[4].id | https://openalex.org/keywords/computer-security |
| keywords[4].score | 0.36478883028030396 |
| keywords[4].display_name | Computer security |
| keywords[5].id | https://openalex.org/keywords/psychology |
| keywords[5].score | 0.2907178997993469 |
| keywords[5].display_name | Psychology |
| keywords[6].id | https://openalex.org/keywords/neuroscience |
| keywords[6].score | 0.06161549687385559 |
| keywords[6].display_name | Neuroscience |
| language | en |
| locations[0].id | doi:10.1609/aaai.v39i6.32619 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210191458 |
| locations[0].source.issn | 2159-5399, 2374-3468 |
| locations[0].source.type | conference |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2159-5399 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| locations[0].source.host_organization | https://openalex.org/P4310320058 |
| locations[0].source.host_organization_name | Association for the Advancement of Artificial Intelligence |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320058 |
| locations[0].source.host_organization_lineage_names | Association for the Advancement of Artificial Intelligence |
| locations[0].license | |
| locations[0].pdf_url | https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774 |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| locations[0].landing_page_url | https://doi.org/10.1609/aaai.v39i6.32619 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5053116259 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-4691-3326 |
| authorships[0].author.display_name | Bin Lü |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Bin Lu |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5102999463 |
| authorships[1].author.orcid | https://orcid.org/0009-0006-2655-6287 |
| authorships[1].author.display_name | Xinyu Xiao |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Xinyu Xiao |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5065694290 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Changzhou Zhang |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Changzhou Zhang |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5052761636 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-1229-3739 |
| authorships[3].author.display_name | Zhou Yang |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Yang Zhou |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5107936461 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Zhiyu Xiang |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Zhiyu Xiang |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5002477413 |
| authorships[5].author.orcid | https://orcid.org/0000-0001-6264-9858 |
| authorships[5].author.display_name | Hangguan Shan |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Hangguan Shan |
| authorships[5].is_corresponding | False |
| authorships[6].author.id | https://openalex.org/A5045424247 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-2344-4283 |
| authorships[6].author.display_name | Eryun Liu |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Eryun Liu |
| authorships[6].is_corresponding | False |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Privacy-Preserving V2X Collaborative Perception Integrating Unknown Collaborators |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10764 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9837999939918518 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Privacy-Preserving Technologies in Data |
| related_works | https://openalex.org/W4391375266, https://openalex.org/W2899084033, https://openalex.org/W2748952813, https://openalex.org/W2390279801, https://openalex.org/W4391913857, https://openalex.org/W2358668433, https://openalex.org/W4396701345, https://openalex.org/W2376932109, https://openalex.org/W2001405890, https://openalex.org/W4396696052 |
| cited_by_count | 0 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1609/aaai.v39i6.32619 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210191458 |
| best_oa_location.source.issn | 2159-5399, 2374-3468 |
| best_oa_location.source.type | conference |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2159-5399 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| best_oa_location.source.host_organization | https://openalex.org/P4310320058 |
| best_oa_location.source.host_organization_name | Association for the Advancement of Artificial Intelligence |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320058 |
| best_oa_location.source.host_organization_lineage_names | Association for the Advancement of Artificial Intelligence |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774 |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| best_oa_location.landing_page_url | https://doi.org/10.1609/aaai.v39i6.32619 |
| primary_location.id | doi:10.1609/aaai.v39i6.32619 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210191458 |
| primary_location.source.issn | 2159-5399, 2374-3468 |
| primary_location.source.type | conference |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2159-5399 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| primary_location.source.host_organization | https://openalex.org/P4310320058 |
| primary_location.source.host_organization_name | Association for the Advancement of Artificial Intelligence |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320058 |
| primary_location.source.host_organization_lineage_names | Association for the Advancement of Artificial Intelligence |
| primary_location.license | |
| primary_location.pdf_url | https://ojs.aaai.org/index.php/AAAI/article/download/32619/34774 |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Proceedings of the AAAI Conference on Artificial Intelligence |
| primary_location.landing_page_url | https://doi.org/10.1609/aaai.v39i6.32619 |
| publication_date | 2025-04-11 |
| publication_year | 2025 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 38, 75, 96, 126, 145, 218 |
| abstract_inverted_index.1) | 168 |
| abstract_inverted_index.2) | 188 |
| abstract_inverted_index.In | 91 |
| abstract_inverted_index.No | 196 |
| abstract_inverted_index.We | 142, 212 |
| abstract_inverted_index.at | 176 |
| abstract_inverted_index.be | 74 |
| abstract_inverted_index.by | 20, 175 |
| abstract_inverted_index.in | 9, 57, 65, 181 |
| abstract_inverted_index.is | 61, 81, 104, 228 |
| abstract_inverted_index.it | 192 |
| abstract_inverted_index.of | 46, 52, 139, 209, 224 |
| abstract_inverted_index.on | 160, 183 |
| abstract_inverted_index.or | 28, 204 |
| abstract_inverted_index.to | 13, 16, 36, 73, 85, 116, 135, 149, 156 |
| abstract_inverted_index.we | 94, 123 |
| abstract_inverted_index.MSD | 169 |
| abstract_inverted_index.all | 53 |
| abstract_inverted_index.and | 42, 60, 63, 83, 88, 111, 164, 179, 185, 201 |
| abstract_inverted_index.but | 78 |
| abstract_inverted_index.can | 202 |
| abstract_inverted_index.due | 12 |
| abstract_inverted_index.ego | 113 |
| abstract_inverted_index.for | 221, 230 |
| abstract_inverted_index.has | 4 |
| abstract_inverted_index.its | 14, 79, 108 |
| abstract_inverted_index.new | 219 |
| abstract_inverted_index.own | 109 |
| abstract_inverted_index.the | 66, 112, 151, 161, 195, 207, 222 |
| abstract_inverted_index.2.8% | 178 |
| abstract_inverted_index.6.7% | 180 |
| abstract_inverted_index.Late | 198 |
| abstract_inverted_index.MSD, | 125 |
| abstract_inverted_index.also | 143 |
| abstract_inverted_index.deep | 34 |
| abstract_inverted_index.e.g. | 26 |
| abstract_inverted_index.each | 102 |
| abstract_inverted_index.even | 205 |
| abstract_inverted_index.from | 23, 153 |
| abstract_inverted_index.fuse | 137 |
| abstract_inverted_index.most | 45 |
| abstract_inverted_index.real | 67 |
| abstract_inverted_index.this | 92 |
| abstract_inverted_index.with | 107, 118, 132 |
| abstract_inverted_index.(V2X) | 1 |
| abstract_inverted_index.AP0.7 | 182 |
| abstract_inverted_index.After | 189 |
| abstract_inverted_index.agent | 103 |
| abstract_inverted_index.align | 150 |
| abstract_inverted_index.joint | 50, 210 |
| abstract_inverted_index.least | 177 |
| abstract_inverted_index.needs | 115 |
| abstract_inverted_index.noise | 87 |
| abstract_inverted_index.other | 24 |
| abstract_inverted_index.scene | 18 |
| abstract_inverted_index.seems | 72 |
| abstract_inverted_index.share | 33 |
| abstract_inverted_index.study | 223 |
| abstract_inverted_index.that: | 167 |
| abstract_inverted_index.these | 47 |
| abstract_inverted_index.truly | 213 |
| abstract_inverted_index.where | 101 |
| abstract_inverted_index.which | 55, 227 |
| abstract_inverted_index.Fusion | 199 |
| abstract_inverted_index.better | 136 |
| abstract_inverted_index.delay. | 90 |
| abstract_inverted_index.direct | 76 |
| abstract_inverted_index.domain | 147, 190 |
| abstract_inverted_index.fusion | 129 |
| abstract_inverted_index.gained | 6 |
| abstract_inverted_index.method | 130 |
| abstract_inverted_index.others | 174 |
| abstract_inverted_index.paper, | 93 |
| abstract_inverted_index.world. | 68 |
| abstract_inverted_index.Fusion, | 197 |
| abstract_inverted_index.Sharing | 69 |
| abstract_inverted_index.ability | 15 |
| abstract_inverted_index.achieve | 37 |
| abstract_inverted_index.adapter | 148 |
| abstract_inverted_index.agents, | 54 |
| abstract_inverted_index.agents. | 141 |
| abstract_inverted_index.between | 40 |
| abstract_inverted_index.crucial | 229 |
| abstract_inverted_index.dataset | 110 |
| abstract_inverted_index.driving | 11 |
| abstract_inverted_index.enhance | 17 |
| abstract_inverted_index.feature | 128 |
| abstract_inverted_index.leakage | 59 |
| abstract_inverted_index.methods | 48 |
| abstract_inverted_index.plug-in | 146 |
| abstract_inverted_index.privacy | 58 |
| abstract_inverted_index.propose | 95, 124, 144 |
| abstract_inverted_index.require | 49 |
| abstract_inverted_index.results | 56, 71 |
| abstract_inverted_index.surpass | 206 |
| abstract_inverted_index.trained | 106 |
| abstract_inverted_index.unknown | 120, 154 |
| abstract_inverted_index.usually | 32 |
| abstract_inverted_index.vehicle | 114 |
| abstract_inverted_index.DAIR-V2X | 163, 184 |
| abstract_inverted_index.Existing | 30 |
| abstract_inverted_index.However, | 44 |
| abstract_inverted_index.V2V4Real | 165 |
| abstract_inverted_index.accuracy | 41 |
| abstract_inverted_index.achieves | 170, 214 |
| abstract_inverted_index.approach | 203 |
| abstract_inverted_index.combined | 131 |
| abstract_inverted_index.features | 35, 138, 152 |
| abstract_inverted_index.paradigm | 220 |
| abstract_inverted_index.recently | 5 |
| abstract_inverted_index.training | 51 |
| abstract_inverted_index.vehicles | 27 |
| abstract_inverted_index.Extensive | 158 |
| abstract_inverted_index.V2V4Real, | 186 |
| abstract_inverted_index.attention | 8 |
| abstract_inverted_index.different | 140 |
| abstract_inverted_index.integrate | 117 |
| abstract_inverted_index.practical | 231 |
| abstract_inverted_index.providing | 217 |
| abstract_inverted_index.scenarios | 200 |
| abstract_inverted_index.sensitive | 84 |
| abstract_inverted_index.solution, | 77 |
| abstract_inverted_index.trade-off | 39 |
| abstract_inverted_index.training. | 211 |
| abstract_inverted_index.algorithms | 31 |
| abstract_inverted_index.attention, | 134 |
| abstract_inverted_index.autonomous | 10 |
| abstract_inverted_index.bandwidth. | 43 |
| abstract_inverted_index.completely | 119 |
| abstract_inverted_index.deformable | 133 |
| abstract_inverted_index.framework, | 100 |
| abstract_inverted_index.increasing | 7 |
| abstract_inverted_index.perception | 3, 99 |
| abstract_inverted_index.prediction | 70 |
| abstract_inverted_index.remarkable | 171 |
| abstract_inverted_index.separately | 105 |
| abstract_inverted_index.suboptimal | 82 |
| abstract_inverted_index.adaptation, | 191 |
| abstract_inverted_index.challenging | 162 |
| abstract_inverted_index.demonstrate | 166 |
| abstract_inverted_index.ego-domain. | 157 |
| abstract_inverted_index.experiments | 159 |
| abstract_inverted_index.impractical | 62 |
| abstract_inverted_index.information | 22 |
| abstract_inverted_index.integrating | 21 |
| abstract_inverted_index.multi-scale | 127 |
| abstract_inverted_index.outperforms | 194 |
| abstract_inverted_index.perception, | 226 |
| abstract_inverted_index.performance | 80, 208 |
| abstract_inverted_index.localization | 86 |
| abstract_inverted_index.performance, | 172 |
| abstract_inverted_index.unacceptable | 64 |
| abstract_inverted_index.Specifically, | 122 |
| abstract_inverted_index.applications. | 232 |
| abstract_inverted_index.collaborative | 2, 98, 225 |
| abstract_inverted_index.collaborators | 155 |
| abstract_inverted_index.communication | 89 |
| abstract_inverted_index.outperforming | 173 |
| abstract_inverted_index.respectively; | 187 |
| abstract_inverted_index.significantly | 193 |
| abstract_inverted_index.understanding | 19 |
| abstract_inverted_index.collaboration, | 216 |
| abstract_inverted_index.collaborators, | 25 |
| abstract_inverted_index.collaborators. | 121 |
| abstract_inverted_index.infrastructure. | 29 |
| abstract_inverted_index.privacy-preserving | 97, 215 |
| abstract_inverted_index.Vehicle-to-everything | 0 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.3839196 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |