Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation Learning Article Swipe
Yuan Yao
,
Chang Liu
,
Dezhao Luo
,
Yu Zhou
,
Qixiang Ye
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2006.11476
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2006.11476
In self-supervised spatio-temporal representation learning, the temporal resolution and long-short term characteristics are not yet fully explored, which limits representation capabilities of learned models. In this paper, we propose a novel self-supervised method, referred to as video Playback Rate Perception (PRP), to learn spatio-temporal representation in a simple-yet-effective way. PRP roots in a dilated sampling strategy, which produces self-supervision signals about video playback rates for representation model learning. PRP is implemented with a feature encoder, a classification module, and a reconstructing decoder, to achieve spatio-temporal semantic retention in a collaborative discrimination-generation manner. The discriminative perception model follows a feature encoder to prefer perceiving low temporal resolution and long-term representation by classifying fast-forward rates. The generative perception model acts as a feature decoder to focus on comprehending high temporal resolution and short-term representation by introducing a motion-attention mechanism. PRP is applied on typical video target tasks including action recognition and video retrieval. Experiments show that PRP outperforms state-of-the-art self-supervised models with significant margins. Code is available at github.com/yuanyao366/PRP
Related Topics
Concepts
Computer science
Feature learning
Discriminative model
Encoder
Artificial intelligence
Representation (politics)
Feature (linguistics)
Generative model
Perception
Pattern recognition (psychology)
Focus (optics)
Code (set theory)
Speech recognition
Generative grammar
Physics
Neuroscience
Philosophy
Programming language
Political science
Linguistics
Optics
Biology
Operating system
Law
Set (abstract data type)
Politics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2006.11476
- https://arxiv.org/pdf/2006.11476
- OA Status
- green
- Cited By
- 1
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3036085800
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W3036085800Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2006.11476Digital Object Identifier
- Title
-
Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation LearningWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-06-20Full publication date if available
- Authors
-
Yuan Yao, Chang Liu, Dezhao Luo, Yu Zhou, Qixiang YeList of authors in order
- Landing page
-
https://arxiv.org/abs/2006.11476Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2006.11476Direct 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/2006.11476Direct OA link when available
- Concepts
-
Computer science, Feature learning, Discriminative model, Encoder, Artificial intelligence, Representation (politics), Feature (linguistics), Generative model, Perception, Pattern recognition (psychology), Focus (optics), Code (set theory), Speech recognition, Generative grammar, Physics, Neuroscience, Philosophy, Programming language, Political science, Linguistics, Optics, Biology, Operating system, Law, Set (abstract data type), PoliticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1Per-year citation counts (last 5 years)
- References (count)
-
41Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W3036085800 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2006.11476 |
| ids.doi | https://doi.org/10.48550/arxiv.2006.11476 |
| ids.mag | 3036085800 |
| ids.openalex | https://openalex.org/W3036085800 |
| fwci | |
| type | preprint |
| title | Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation Learning |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10812 |
| 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 | Human Pose and Action Recognition |
| topics[1].id | https://openalex.org/T10531 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9954000115394592 |
| 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 | Advanced Vision and Imaging |
| topics[2].id | https://openalex.org/T11714 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9905999898910522 |
| 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 | Multimodal Machine Learning Applications |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7771010398864746 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C59404180 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7122757434844971 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q17013334 |
| concepts[1].display_name | Feature learning |
| concepts[2].id | https://openalex.org/C97931131 |
| concepts[2].level | 2 |
| concepts[2].score | 0.7016355991363525 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q5282087 |
| concepts[2].display_name | Discriminative model |
| concepts[3].id | https://openalex.org/C118505674 |
| concepts[3].level | 2 |
| concepts[3].score | 0.677791953086853 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q42586063 |
| concepts[3].display_name | Encoder |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.6742813587188721 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C2776359362 |
| concepts[5].level | 3 |
| concepts[5].score | 0.6418328881263733 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2145286 |
| concepts[5].display_name | Representation (politics) |
| concepts[6].id | https://openalex.org/C2776401178 |
| concepts[6].level | 2 |
| concepts[6].score | 0.6160535216331482 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q12050496 |
| concepts[6].display_name | Feature (linguistics) |
| concepts[7].id | https://openalex.org/C167966045 |
| concepts[7].level | 3 |
| concepts[7].score | 0.5978057980537415 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q5532625 |
| concepts[7].display_name | Generative model |
| concepts[8].id | https://openalex.org/C26760741 |
| concepts[8].level | 2 |
| concepts[8].score | 0.5235597491264343 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q160402 |
| concepts[8].display_name | Perception |
| concepts[9].id | https://openalex.org/C153180895 |
| concepts[9].level | 2 |
| concepts[9].score | 0.49442458152770996 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[9].display_name | Pattern recognition (psychology) |
| concepts[10].id | https://openalex.org/C192209626 |
| concepts[10].level | 2 |
| concepts[10].score | 0.4638272523880005 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q190909 |
| concepts[10].display_name | Focus (optics) |
| concepts[11].id | https://openalex.org/C2776760102 |
| concepts[11].level | 3 |
| concepts[11].score | 0.4344606101512909 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q5139990 |
| concepts[11].display_name | Code (set theory) |
| concepts[12].id | https://openalex.org/C28490314 |
| concepts[12].level | 1 |
| concepts[12].score | 0.3261563777923584 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q189436 |
| concepts[12].display_name | Speech recognition |
| concepts[13].id | https://openalex.org/C39890363 |
| concepts[13].level | 2 |
| concepts[13].score | 0.2862105369567871 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q36108 |
| concepts[13].display_name | Generative grammar |
| concepts[14].id | https://openalex.org/C121332964 |
| concepts[14].level | 0 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[14].display_name | Physics |
| concepts[15].id | https://openalex.org/C169760540 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q207011 |
| concepts[15].display_name | Neuroscience |
| concepts[16].id | https://openalex.org/C138885662 |
| concepts[16].level | 0 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[16].display_name | Philosophy |
| concepts[17].id | https://openalex.org/C199360897 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[17].display_name | Programming language |
| concepts[18].id | https://openalex.org/C17744445 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q36442 |
| concepts[18].display_name | Political science |
| concepts[19].id | https://openalex.org/C41895202 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q8162 |
| concepts[19].display_name | Linguistics |
| concepts[20].id | https://openalex.org/C120665830 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q14620 |
| concepts[20].display_name | Optics |
| concepts[21].id | https://openalex.org/C86803240 |
| concepts[21].level | 0 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[21].display_name | Biology |
| concepts[22].id | https://openalex.org/C111919701 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[22].display_name | Operating system |
| concepts[23].id | https://openalex.org/C199539241 |
| concepts[23].level | 1 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q7748 |
| concepts[23].display_name | Law |
| concepts[24].id | https://openalex.org/C177264268 |
| concepts[24].level | 2 |
| concepts[24].score | 0.0 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q1514741 |
| concepts[24].display_name | Set (abstract data type) |
| concepts[25].id | https://openalex.org/C94625758 |
| concepts[25].level | 2 |
| concepts[25].score | 0.0 |
| concepts[25].wikidata | https://www.wikidata.org/wiki/Q7163 |
| concepts[25].display_name | Politics |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.7771010398864746 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/feature-learning |
| keywords[1].score | 0.7122757434844971 |
| keywords[1].display_name | Feature learning |
| keywords[2].id | https://openalex.org/keywords/discriminative-model |
| keywords[2].score | 0.7016355991363525 |
| keywords[2].display_name | Discriminative model |
| keywords[3].id | https://openalex.org/keywords/encoder |
| keywords[3].score | 0.677791953086853 |
| keywords[3].display_name | Encoder |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.6742813587188721 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/representation |
| keywords[5].score | 0.6418328881263733 |
| keywords[5].display_name | Representation (politics) |
| keywords[6].id | https://openalex.org/keywords/feature |
| keywords[6].score | 0.6160535216331482 |
| keywords[6].display_name | Feature (linguistics) |
| keywords[7].id | https://openalex.org/keywords/generative-model |
| keywords[7].score | 0.5978057980537415 |
| keywords[7].display_name | Generative model |
| keywords[8].id | https://openalex.org/keywords/perception |
| keywords[8].score | 0.5235597491264343 |
| keywords[8].display_name | Perception |
| keywords[9].id | https://openalex.org/keywords/pattern-recognition |
| keywords[9].score | 0.49442458152770996 |
| keywords[9].display_name | Pattern recognition (psychology) |
| keywords[10].id | https://openalex.org/keywords/focus |
| keywords[10].score | 0.4638272523880005 |
| keywords[10].display_name | Focus (optics) |
| keywords[11].id | https://openalex.org/keywords/code |
| keywords[11].score | 0.4344606101512909 |
| keywords[11].display_name | Code (set theory) |
| keywords[12].id | https://openalex.org/keywords/speech-recognition |
| keywords[12].score | 0.3261563777923584 |
| keywords[12].display_name | Speech recognition |
| keywords[13].id | https://openalex.org/keywords/generative-grammar |
| keywords[13].score | 0.2862105369567871 |
| keywords[13].display_name | Generative grammar |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2006.11476 |
| 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/2006.11476 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | |
| 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/2006.11476 |
| locations[1].id | doi:10.48550/arxiv.2006.11476 |
| 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.2006.11476 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5103072099 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-3616-2496 |
| authorships[0].author.display_name | Yuan Yao |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210165038 |
| authorships[0].affiliations[0].raw_affiliation_string | University of the Chinese Academy of Sciences; |
| authorships[0].institutions[0].id | https://openalex.org/I4210165038 |
| authorships[0].institutions[0].ror | https://ror.org/05qbk4x57 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | University of Chinese Academy of Sciences |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Yuan Yao |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | University of the Chinese Academy of Sciences; |
| authorships[1].author.id | https://openalex.org/A5008100904 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Chang Liu |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I4210165038 |
| authorships[1].affiliations[0].raw_affiliation_string | University of the Chinese Academy of Sciences; |
| authorships[1].institutions[0].id | https://openalex.org/I4210165038 |
| authorships[1].institutions[0].ror | https://ror.org/05qbk4x57 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | University of Chinese Academy of Sciences |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Chang Liu |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | University of the Chinese Academy of Sciences; |
| authorships[2].author.id | https://openalex.org/A5052937695 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Dezhao Luo |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210156404 |
| authorships[2].affiliations[0].raw_affiliation_string | [Institute of Information Engineering, Chinese Academy of Sciences] |
| authorships[2].institutions[0].id | https://openalex.org/I19820366 |
| authorships[2].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[2].institutions[0].type | government |
| authorships[2].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[2].institutions[1].id | https://openalex.org/I4210156404 |
| authorships[2].institutions[1].ror | https://ror.org/04r53se39 |
| authorships[2].institutions[1].type | facility |
| authorships[2].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210156404 |
| authorships[2].institutions[1].country_code | CN |
| authorships[2].institutions[1].display_name | Institute of Information Engineering |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Dezhao Luo |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | [Institute of Information Engineering, Chinese Academy of Sciences] |
| authorships[3].author.id | https://openalex.org/A5016175345 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-4188-9953 |
| authorships[3].author.display_name | Yu Zhou |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I19820366, https://openalex.org/I4210156404 |
| authorships[3].affiliations[0].raw_affiliation_string | [Institute of Information Engineering, Chinese Academy of Sciences] |
| authorships[3].institutions[0].id | https://openalex.org/I19820366 |
| authorships[3].institutions[0].ror | https://ror.org/034t30j35 |
| authorships[3].institutions[0].type | government |
| authorships[3].institutions[0].lineage | https://openalex.org/I19820366 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Chinese Academy of Sciences |
| authorships[3].institutions[1].id | https://openalex.org/I4210156404 |
| authorships[3].institutions[1].ror | https://ror.org/04r53se39 |
| authorships[3].institutions[1].type | facility |
| authorships[3].institutions[1].lineage | https://openalex.org/I19820366, https://openalex.org/I4210156404 |
| authorships[3].institutions[1].country_code | CN |
| authorships[3].institutions[1].display_name | Institute of Information Engineering |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Yu Zhou |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | [Institute of Information Engineering, Chinese Academy of Sciences] |
| authorships[4].author.id | https://openalex.org/A5015317495 |
| authorships[4].author.orcid | |
| authorships[4].author.display_name | Qixiang Ye |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210165038 |
| authorships[4].affiliations[0].raw_affiliation_string | University of the Chinese Academy of Sciences; |
| authorships[4].institutions[0].id | https://openalex.org/I4210165038 |
| authorships[4].institutions[0].ror | https://ror.org/05qbk4x57 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I19820366, https://openalex.org/I4210165038 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | University of Chinese Academy of Sciences |
| authorships[4].author_position | last |
| authorships[4].raw_author_name | Qixiang Ye |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | University of the Chinese Academy of Sciences; |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2006.11476 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Video Playback Rate Perception for Self-supervisedSpatio-Temporal Representation Learning |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T10812 |
| 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 | Human Pose and Action Recognition |
| related_works | https://openalex.org/W2093104230, https://openalex.org/W4390874210, https://openalex.org/W4384918963, https://openalex.org/W2128027845, https://openalex.org/W4386184937, https://openalex.org/W1493875009, https://openalex.org/W4388844349, https://openalex.org/W2105231718, https://openalex.org/W2153939756, https://openalex.org/W2019680624 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2023 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2006.11476 |
| 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/2006.11476 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | |
| 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/2006.11476 |
| primary_location.id | pmh:oai:arXiv.org:2006.11476 |
| 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/2006.11476 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | |
| 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/2006.11476 |
| publication_date | 2020-06-20 |
| publication_year | 2020 |
| referenced_works | https://openalex.org/W343636949, https://openalex.org/W2963631366, https://openalex.org/W219040644, https://openalex.org/W2594156432, https://openalex.org/W2403757143, https://openalex.org/W1522734439, https://openalex.org/W2341058432, https://openalex.org/W2963814513, https://openalex.org/W1959608418, https://openalex.org/W2963420272, https://openalex.org/W2766042539, https://openalex.org/W2108598243, https://openalex.org/W2126579184, https://openalex.org/W2520707650, https://openalex.org/W2990503944, https://openalex.org/W2045192497, https://openalex.org/W2963155035, https://openalex.org/W2914438239, https://openalex.org/W1979741733, https://openalex.org/W2962742544, https://openalex.org/W24089286, https://openalex.org/W2963749571, https://openalex.org/W2599837529, https://openalex.org/W2321533354, https://openalex.org/W2550462002, https://openalex.org/W2990873191, https://openalex.org/W2970575838, https://openalex.org/W2619697695, https://openalex.org/W2948467580, https://openalex.org/W2561238782, https://openalex.org/W2163605009, https://openalex.org/W2804078698, https://openalex.org/W2619947201, https://openalex.org/W2575671312, https://openalex.org/W2883451034, https://openalex.org/W2989980422, https://openalex.org/W2342662179, https://openalex.org/W2963826423, https://openalex.org/W2964037671, https://openalex.org/W2948242301, https://openalex.org/W2487442924 |
| referenced_works_count | 41 |
| abstract_inverted_index.a | 29, 46, 52, 72, 75, 79, 88, 97, 119, 134 |
| abstract_inverted_index.In | 0, 24 |
| abstract_inverted_index.as | 35, 118 |
| abstract_inverted_index.at | 165 |
| abstract_inverted_index.by | 109, 132 |
| abstract_inverted_index.in | 45, 51, 87 |
| abstract_inverted_index.is | 69, 138, 163 |
| abstract_inverted_index.of | 21 |
| abstract_inverted_index.on | 124, 140 |
| abstract_inverted_index.to | 34, 41, 82, 100, 122 |
| abstract_inverted_index.we | 27 |
| abstract_inverted_index.PRP | 49, 68, 137, 154 |
| abstract_inverted_index.The | 92, 113 |
| abstract_inverted_index.and | 8, 78, 106, 129, 148 |
| abstract_inverted_index.are | 12 |
| abstract_inverted_index.for | 64 |
| abstract_inverted_index.low | 103 |
| abstract_inverted_index.not | 13 |
| abstract_inverted_index.the | 5 |
| abstract_inverted_index.yet | 14 |
| abstract_inverted_index.Code | 162 |
| abstract_inverted_index.Rate | 38 |
| abstract_inverted_index.acts | 117 |
| abstract_inverted_index.high | 126 |
| abstract_inverted_index.show | 152 |
| abstract_inverted_index.term | 10 |
| abstract_inverted_index.that | 153 |
| abstract_inverted_index.this | 25 |
| abstract_inverted_index.way. | 48 |
| abstract_inverted_index.with | 71, 159 |
| abstract_inverted_index.about | 60 |
| abstract_inverted_index.focus | 123 |
| abstract_inverted_index.fully | 15 |
| abstract_inverted_index.learn | 42 |
| abstract_inverted_index.model | 66, 95, 116 |
| abstract_inverted_index.novel | 30 |
| abstract_inverted_index.rates | 63 |
| abstract_inverted_index.roots | 50 |
| abstract_inverted_index.tasks | 144 |
| abstract_inverted_index.video | 36, 61, 142, 149 |
| abstract_inverted_index.which | 17, 56 |
| abstract_inverted_index.(PRP), | 40 |
| abstract_inverted_index.action | 146 |
| abstract_inverted_index.limits | 18 |
| abstract_inverted_index.models | 158 |
| abstract_inverted_index.paper, | 26 |
| abstract_inverted_index.prefer | 101 |
| abstract_inverted_index.rates. | 112 |
| abstract_inverted_index.target | 143 |
| abstract_inverted_index.achieve | 83 |
| abstract_inverted_index.applied | 139 |
| abstract_inverted_index.decoder | 121 |
| abstract_inverted_index.dilated | 53 |
| abstract_inverted_index.encoder | 99 |
| abstract_inverted_index.feature | 73, 98, 120 |
| abstract_inverted_index.follows | 96 |
| abstract_inverted_index.learned | 22 |
| abstract_inverted_index.manner. | 91 |
| abstract_inverted_index.method, | 32 |
| abstract_inverted_index.models. | 23 |
| abstract_inverted_index.module, | 77 |
| abstract_inverted_index.propose | 28 |
| abstract_inverted_index.signals | 59 |
| abstract_inverted_index.typical | 141 |
| abstract_inverted_index.Playback | 37 |
| abstract_inverted_index.decoder, | 81 |
| abstract_inverted_index.encoder, | 74 |
| abstract_inverted_index.margins. | 161 |
| abstract_inverted_index.playback | 62 |
| abstract_inverted_index.produces | 57 |
| abstract_inverted_index.referred | 33 |
| abstract_inverted_index.sampling | 54 |
| abstract_inverted_index.semantic | 85 |
| abstract_inverted_index.temporal | 6, 104, 127 |
| abstract_inverted_index.available | 164 |
| abstract_inverted_index.explored, | 16 |
| abstract_inverted_index.including | 145 |
| abstract_inverted_index.learning, | 4 |
| abstract_inverted_index.learning. | 67 |
| abstract_inverted_index.long-term | 107 |
| abstract_inverted_index.retention | 86 |
| abstract_inverted_index.strategy, | 55 |
| abstract_inverted_index.Perception | 39 |
| abstract_inverted_index.generative | 114 |
| abstract_inverted_index.long-short | 9 |
| abstract_inverted_index.mechanism. | 136 |
| abstract_inverted_index.perceiving | 102 |
| abstract_inverted_index.perception | 94, 115 |
| abstract_inverted_index.resolution | 7, 105, 128 |
| abstract_inverted_index.retrieval. | 150 |
| abstract_inverted_index.short-term | 130 |
| abstract_inverted_index.Experiments | 151 |
| abstract_inverted_index.classifying | 110 |
| abstract_inverted_index.implemented | 70 |
| abstract_inverted_index.introducing | 133 |
| abstract_inverted_index.outperforms | 155 |
| abstract_inverted_index.recognition | 147 |
| abstract_inverted_index.significant | 160 |
| abstract_inverted_index.capabilities | 20 |
| abstract_inverted_index.fast-forward | 111 |
| abstract_inverted_index.collaborative | 89 |
| abstract_inverted_index.comprehending | 125 |
| abstract_inverted_index.classification | 76 |
| abstract_inverted_index.discriminative | 93 |
| abstract_inverted_index.reconstructing | 80 |
| abstract_inverted_index.representation | 3, 19, 44, 65, 108, 131 |
| abstract_inverted_index.characteristics | 11 |
| abstract_inverted_index.self-supervised | 1, 31, 157 |
| abstract_inverted_index.spatio-temporal | 2, 43, 84 |
| abstract_inverted_index.motion-attention | 135 |
| abstract_inverted_index.self-supervision | 58 |
| abstract_inverted_index.state-of-the-art | 156 |
| abstract_inverted_index.simple-yet-effective | 47 |
| abstract_inverted_index.discrimination-generation | 90 |
| abstract_inverted_index.github.com/yuanyao366/PRP | 166 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/10 |
| sustainable_development_goals[0].score | 0.6499999761581421 |
| sustainable_development_goals[0].display_name | Reduced inequalities |
| citation_normalized_percentile |