DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation Article Swipe
Chen Wang
,
Haochen Shi
,
Weizhuo Wang
,
Ruohan Zhang
,
Li Fei-Fei
,
C. Karen Liu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.07788
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2403.07788
Imitation learning from human hand motion data presents a promising avenue for imbuing robots with human-like dexterity in real-world manipulation tasks. Despite this potential, substantial challenges persist, particularly with the portability of existing hand motion capture (mocap) systems and the complexity of translating mocap data into effective robotic policies. To tackle these issues, we introduce DexCap, a portable hand motion capture system, alongside DexIL, a novel imitation algorithm for training dexterous robot skills directly from human hand mocap data. DexCap offers precise, occlusion-resistant tracking of wrist and finger motions based on SLAM and electromagnetic field together with 3D observations of the environment. Utilizing this rich dataset, DexIL employs inverse kinematics and point cloud-based imitation learning to seamlessly replicate human actions with robot hands. Beyond direct learning from human motion, DexCap also offers an optional human-in-the-loop correction mechanism during policy rollouts to refine and further improve task performance. Through extensive evaluation across six challenging dexterous manipulation tasks, our approach not only demonstrates superior performance but also showcases the system's capability to effectively learn from in-the-wild mocap data, paving the way for future data collection methods in the pursuit of human-level robot dexterity. More details can be found at https://dex-cap.github.io
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2403.07788
- https://arxiv.org/pdf/2403.07788
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392781371
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4392781371Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2403.07788Digital Object Identifier
- Title
-
DexCap: Scalable and Portable Mocap Data Collection System for Dexterous ManipulationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-03-12Full publication date if available
- Authors
-
Chen Wang, Haochen Shi, Weizhuo Wang, Ruohan Zhang, Li Fei-Fei, C. Karen LiuList of authors in order
- Landing page
-
https://arxiv.org/abs/2403.07788Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2403.07788Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2403.07788Direct OA link when available
- Concepts
-
Scalability, Data collection, Computer science, Data collection system, Motion capture, Computer graphics (images), Human–computer interaction, Computer vision, Artificial intelligence, Database, Motion (physics), Mathematics, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4392781371 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2403.07788 |
| ids.doi | https://doi.org/10.48550/arxiv.2403.07788 |
| ids.openalex | https://openalex.org/W4392781371 |
| fwci | |
| type | preprint |
| title | DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10653 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9952999949455261 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2207 |
| topics[0].subfield.display_name | Control and Systems Engineering |
| topics[0].display_name | Robot Manipulation and Learning |
| topics[1].id | https://openalex.org/T11687 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9778000116348267 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2210 |
| topics[1].subfield.display_name | Mechanical Engineering |
| topics[1].display_name | Teleoperation and Haptic Systems |
| topics[2].id | https://openalex.org/T11398 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9498999714851379 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1709 |
| topics[2].subfield.display_name | Human-Computer Interaction |
| topics[2].display_name | Hand Gesture Recognition Systems |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C48044578 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6003233790397644 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q727490 |
| concepts[0].display_name | Scalability |
| concepts[1].id | https://openalex.org/C133462117 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5741364359855652 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q4929239 |
| concepts[1].display_name | Data collection |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5683584809303284 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C2776224087 |
| concepts[3].level | 3 |
| concepts[3].score | 0.4481724798679352 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q28454366 |
| concepts[3].display_name | Data collection system |
| concepts[4].id | https://openalex.org/C48007421 |
| concepts[4].level | 3 |
| concepts[4].score | 0.4328262209892273 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q676252 |
| concepts[4].display_name | Motion capture |
| concepts[5].id | https://openalex.org/C121684516 |
| concepts[5].level | 1 |
| concepts[5].score | 0.4060054421424866 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7600677 |
| concepts[5].display_name | Computer graphics (images) |
| concepts[6].id | https://openalex.org/C107457646 |
| concepts[6].level | 1 |
| concepts[6].score | 0.387671560049057 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q207434 |
| concepts[6].display_name | Human–computer interaction |
| concepts[7].id | https://openalex.org/C31972630 |
| concepts[7].level | 1 |
| concepts[7].score | 0.34329700469970703 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q844240 |
| concepts[7].display_name | Computer vision |
| concepts[8].id | https://openalex.org/C154945302 |
| concepts[8].level | 1 |
| concepts[8].score | 0.33751949667930603 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[8].display_name | Artificial intelligence |
| concepts[9].id | https://openalex.org/C77088390 |
| concepts[9].level | 1 |
| concepts[9].score | 0.19475534558296204 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q8513 |
| concepts[9].display_name | Database |
| concepts[10].id | https://openalex.org/C104114177 |
| concepts[10].level | 2 |
| concepts[10].score | 0.10400128364562988 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q79782 |
| concepts[10].display_name | Motion (physics) |
| concepts[11].id | https://openalex.org/C33923547 |
| concepts[11].level | 0 |
| concepts[11].score | 0.08269703388214111 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[11].display_name | Mathematics |
| concepts[12].id | https://openalex.org/C105795698 |
| concepts[12].level | 1 |
| concepts[12].score | 0.0 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[12].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/scalability |
| keywords[0].score | 0.6003233790397644 |
| keywords[0].display_name | Scalability |
| keywords[1].id | https://openalex.org/keywords/data-collection |
| keywords[1].score | 0.5741364359855652 |
| keywords[1].display_name | Data collection |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.5683584809303284 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/data-collection-system |
| keywords[3].score | 0.4481724798679352 |
| keywords[3].display_name | Data collection system |
| keywords[4].id | https://openalex.org/keywords/motion-capture |
| keywords[4].score | 0.4328262209892273 |
| keywords[4].display_name | Motion capture |
| keywords[5].id | https://openalex.org/keywords/computer-graphics |
| keywords[5].score | 0.4060054421424866 |
| keywords[5].display_name | Computer graphics (images) |
| keywords[6].id | https://openalex.org/keywords/human–computer-interaction |
| keywords[6].score | 0.387671560049057 |
| keywords[6].display_name | Human–computer interaction |
| keywords[7].id | https://openalex.org/keywords/computer-vision |
| keywords[7].score | 0.34329700469970703 |
| keywords[7].display_name | Computer vision |
| keywords[8].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[8].score | 0.33751949667930603 |
| keywords[8].display_name | Artificial intelligence |
| keywords[9].id | https://openalex.org/keywords/database |
| keywords[9].score | 0.19475534558296204 |
| keywords[9].display_name | Database |
| keywords[10].id | https://openalex.org/keywords/motion |
| keywords[10].score | 0.10400128364562988 |
| keywords[10].display_name | Motion (physics) |
| keywords[11].id | https://openalex.org/keywords/mathematics |
| keywords[11].score | 0.08269703388214111 |
| keywords[11].display_name | Mathematics |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2403.07788 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2403.07788 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2403.07788 |
| locations[1].id | doi:10.48550/arxiv.2403.07788 |
| 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 | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2403.07788 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5100337522 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-9737-1673 |
| authorships[0].author.display_name | Chen Wang |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Wang, Chen |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5066687788 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-9999-8979 |
| authorships[1].author.display_name | Haochen Shi |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Shi, Haochen |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5070628412 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-1225-4011 |
| authorships[2].author.display_name | Weizhuo Wang |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Wang, Weizhuo |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5101649950 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-6681-3360 |
| authorships[3].author.display_name | Ruohan Zhang |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Zhang, Ruohan |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5100450462 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-7481-0810 |
| authorships[4].author.display_name | Li Fei-Fei |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Fei-Fei, Li |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5037138883 |
| authorships[5].author.orcid | https://orcid.org/0009-0001-3449-9714 |
| authorships[5].author.display_name | C. Karen Liu |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | Liu, C. Karen |
| authorships[5].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://arxiv.org/pdf/2403.07788 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2024-03-14T00:00:00 |
| display_name | DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10653 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9952999949455261 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2207 |
| primary_topic.subfield.display_name | Control and Systems Engineering |
| primary_topic.display_name | Robot Manipulation and Learning |
| related_works | https://openalex.org/W2350321095, https://openalex.org/W2264071816, https://openalex.org/W4298353262, https://openalex.org/W2357727677, https://openalex.org/W2330001192, https://openalex.org/W2355548227, https://openalex.org/W2393464810, https://openalex.org/W3214861872, https://openalex.org/W2352157870, https://openalex.org/W4301041291 |
| cited_by_count | 2 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2403.07788 |
| 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/2403.07788 |
| 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/2403.07788 |
| primary_location.id | pmh:oai:arXiv.org:2403.07788 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2403.07788 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2403.07788 |
| publication_date | 2024-03-12 |
| publication_year | 2024 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 8, 56, 64 |
| abstract_inverted_index.3D | 97 |
| abstract_inverted_index.To | 49 |
| abstract_inverted_index.an | 132 |
| abstract_inverted_index.at | 196 |
| abstract_inverted_index.be | 194 |
| abstract_inverted_index.in | 17, 184 |
| abstract_inverted_index.of | 31, 41, 84, 99, 187 |
| abstract_inverted_index.on | 90 |
| abstract_inverted_index.to | 115, 140, 169 |
| abstract_inverted_index.we | 53 |
| abstract_inverted_index.and | 38, 86, 92, 110, 142 |
| abstract_inverted_index.but | 163 |
| abstract_inverted_index.can | 193 |
| abstract_inverted_index.for | 11, 68, 179 |
| abstract_inverted_index.not | 158 |
| abstract_inverted_index.our | 156 |
| abstract_inverted_index.six | 151 |
| abstract_inverted_index.the | 29, 39, 100, 166, 177, 185 |
| abstract_inverted_index.way | 178 |
| abstract_inverted_index.More | 191 |
| abstract_inverted_index.SLAM | 91 |
| abstract_inverted_index.also | 130, 164 |
| abstract_inverted_index.data | 6, 44, 181 |
| abstract_inverted_index.from | 2, 74, 126, 172 |
| abstract_inverted_index.hand | 4, 33, 58, 76 |
| abstract_inverted_index.into | 45 |
| abstract_inverted_index.only | 159 |
| abstract_inverted_index.rich | 104 |
| abstract_inverted_index.task | 145 |
| abstract_inverted_index.this | 22, 103 |
| abstract_inverted_index.with | 14, 28, 96, 120 |
| abstract_inverted_index.DexIL | 106 |
| abstract_inverted_index.based | 89 |
| abstract_inverted_index.data, | 175 |
| abstract_inverted_index.data. | 78 |
| abstract_inverted_index.field | 94 |
| abstract_inverted_index.found | 195 |
| abstract_inverted_index.human | 3, 75, 118, 127 |
| abstract_inverted_index.learn | 171 |
| abstract_inverted_index.mocap | 43, 77, 174 |
| abstract_inverted_index.novel | 65 |
| abstract_inverted_index.point | 111 |
| abstract_inverted_index.robot | 71, 121, 189 |
| abstract_inverted_index.these | 51 |
| abstract_inverted_index.wrist | 85 |
| abstract_inverted_index.Beyond | 123 |
| abstract_inverted_index.DexCap | 79, 129 |
| abstract_inverted_index.DexIL, | 63 |
| abstract_inverted_index.across | 150 |
| abstract_inverted_index.avenue | 10 |
| abstract_inverted_index.direct | 124 |
| abstract_inverted_index.during | 137 |
| abstract_inverted_index.finger | 87 |
| abstract_inverted_index.future | 180 |
| abstract_inverted_index.hands. | 122 |
| abstract_inverted_index.motion | 5, 34, 59 |
| abstract_inverted_index.offers | 80, 131 |
| abstract_inverted_index.paving | 176 |
| abstract_inverted_index.policy | 138 |
| abstract_inverted_index.refine | 141 |
| abstract_inverted_index.robots | 13 |
| abstract_inverted_index.skills | 72 |
| abstract_inverted_index.tackle | 50 |
| abstract_inverted_index.tasks, | 155 |
| abstract_inverted_index.tasks. | 20 |
| abstract_inverted_index.(mocap) | 36 |
| abstract_inverted_index.Despite | 21 |
| abstract_inverted_index.DexCap, | 55 |
| abstract_inverted_index.Through | 147 |
| abstract_inverted_index.actions | 119 |
| abstract_inverted_index.capture | 35, 60 |
| abstract_inverted_index.details | 192 |
| abstract_inverted_index.employs | 107 |
| abstract_inverted_index.further | 143 |
| abstract_inverted_index.imbuing | 12 |
| abstract_inverted_index.improve | 144 |
| abstract_inverted_index.inverse | 108 |
| abstract_inverted_index.issues, | 52 |
| abstract_inverted_index.methods | 183 |
| abstract_inverted_index.motion, | 128 |
| abstract_inverted_index.motions | 88 |
| abstract_inverted_index.pursuit | 186 |
| abstract_inverted_index.robotic | 47 |
| abstract_inverted_index.system, | 61 |
| abstract_inverted_index.systems | 37 |
| abstract_inverted_index.approach | 157 |
| abstract_inverted_index.dataset, | 105 |
| abstract_inverted_index.directly | 73 |
| abstract_inverted_index.existing | 32 |
| abstract_inverted_index.learning | 1, 114, 125 |
| abstract_inverted_index.optional | 133 |
| abstract_inverted_index.persist, | 26 |
| abstract_inverted_index.portable | 57 |
| abstract_inverted_index.precise, | 81 |
| abstract_inverted_index.presents | 7 |
| abstract_inverted_index.rollouts | 139 |
| abstract_inverted_index.superior | 161 |
| abstract_inverted_index.system's | 167 |
| abstract_inverted_index.together | 95 |
| abstract_inverted_index.tracking | 83 |
| abstract_inverted_index.training | 69 |
| abstract_inverted_index.Imitation | 0 |
| abstract_inverted_index.Utilizing | 102 |
| abstract_inverted_index.algorithm | 67 |
| abstract_inverted_index.alongside | 62 |
| abstract_inverted_index.dexterity | 16 |
| abstract_inverted_index.dexterous | 70, 153 |
| abstract_inverted_index.effective | 46 |
| abstract_inverted_index.extensive | 148 |
| abstract_inverted_index.imitation | 66, 113 |
| abstract_inverted_index.introduce | 54 |
| abstract_inverted_index.mechanism | 136 |
| abstract_inverted_index.policies. | 48 |
| abstract_inverted_index.promising | 9 |
| abstract_inverted_index.replicate | 117 |
| abstract_inverted_index.showcases | 165 |
| abstract_inverted_index.capability | 168 |
| abstract_inverted_index.challenges | 25 |
| abstract_inverted_index.collection | 182 |
| abstract_inverted_index.complexity | 40 |
| abstract_inverted_index.correction | 135 |
| abstract_inverted_index.dexterity. | 190 |
| abstract_inverted_index.evaluation | 149 |
| abstract_inverted_index.human-like | 15 |
| abstract_inverted_index.kinematics | 109 |
| abstract_inverted_index.potential, | 23 |
| abstract_inverted_index.real-world | 18 |
| abstract_inverted_index.seamlessly | 116 |
| abstract_inverted_index.challenging | 152 |
| abstract_inverted_index.cloud-based | 112 |
| abstract_inverted_index.effectively | 170 |
| abstract_inverted_index.human-level | 188 |
| abstract_inverted_index.in-the-wild | 173 |
| abstract_inverted_index.performance | 162 |
| abstract_inverted_index.portability | 30 |
| abstract_inverted_index.substantial | 24 |
| abstract_inverted_index.translating | 42 |
| abstract_inverted_index.demonstrates | 160 |
| abstract_inverted_index.environment. | 101 |
| abstract_inverted_index.manipulation | 19, 154 |
| abstract_inverted_index.observations | 98 |
| abstract_inverted_index.particularly | 27 |
| abstract_inverted_index.performance. | 146 |
| abstract_inverted_index.electromagnetic | 93 |
| abstract_inverted_index.human-in-the-loop | 134 |
| abstract_inverted_index.occlusion-resistant | 82 |
| abstract_inverted_index.https://dex-cap.github.io | 197 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |