Detecting and Recognizing Human-Object Interactions Article Swipe
Georgia Gkioxari
,
Ross Girshick
,
Piotr Dollár
,
Kaiming He
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1704.07333
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1704.07333
To understand the visual world, a machine must not only recognize individual object instances but also how they interact. Humans are often at the center of such interactions and detecting human-object interactions is an important practical and scientific problem. In this paper, we address the task of detecting triplets in challenging everyday photos. We propose a novel model that is driven by a human-centric approach. Our hypothesis is that the appearance of a person -- their pose, clothing, action -- is a powerful cue for localizing the objects they are interacting with. To exploit this cue, our model learns to predict an action-specific density over target object locations based on the appearance of a detected person. Our model also jointly learns to detect people and objects, and by fusing these predictions it efficiently infers interaction triplets in a clean, jointly trained end-to-end system we call InteractNet. We validate our approach on the recently introduced Verbs in COCO (V-COCO) and HICO-DET datasets, where we show quantitatively compelling results.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1704.07333
- https://arxiv.org/pdf/1704.07333
- OA Status
- green
- Cited By
- 60
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2608915011
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https://openalex.org/W2608915011Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1704.07333Digital Object Identifier
- Title
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Detecting and Recognizing Human-Object InteractionsWork title
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
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2017-04-24Full publication date if available
- Authors
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Georgia Gkioxari, Ross Girshick, Piotr Dollár, Kaiming HeList of authors in order
- Landing page
-
https://arxiv.org/abs/1704.07333Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1704.07333Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/1704.07333Direct OA link when available
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Computer science, Object (grammar), Artificial intelligence, Action (physics), Task (project management), Exploit, Machine learning, Computer vision, Computer security, Physics, Economics, Management, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
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60Total citation count in OpenAlex
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2025: 1, 2024: 5, 2023: 8, 2022: 4, 2021: 10Per-year citation counts (last 5 years)
- References (count)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.such | 26 |
| abstract_inverted_index.task | 45 |
| abstract_inverted_index.that | 58, 68 |
| abstract_inverted_index.they | 17, 88 |
| abstract_inverted_index.this | 40, 94 |
| abstract_inverted_index.Verbs | 154 |
| abstract_inverted_index.based | 108 |
| abstract_inverted_index.model | 57, 97, 117 |
| abstract_inverted_index.novel | 56 |
| abstract_inverted_index.often | 21 |
| abstract_inverted_index.pose, | 76 |
| abstract_inverted_index.their | 75 |
| abstract_inverted_index.these | 129 |
| abstract_inverted_index.where | 161 |
| abstract_inverted_index.with. | 91 |
| abstract_inverted_index.Humans | 19 |
| abstract_inverted_index.action | 78 |
| abstract_inverted_index.center | 24 |
| abstract_inverted_index.clean, | 138 |
| abstract_inverted_index.detect | 122 |
| abstract_inverted_index.driven | 60 |
| abstract_inverted_index.fusing | 128 |
| abstract_inverted_index.infers | 133 |
| abstract_inverted_index.learns | 98, 120 |
| abstract_inverted_index.object | 12, 106 |
| abstract_inverted_index.paper, | 41 |
| abstract_inverted_index.people | 123 |
| abstract_inverted_index.person | 73 |
| abstract_inverted_index.system | 142 |
| abstract_inverted_index.target | 105 |
| abstract_inverted_index.visual | 3 |
| abstract_inverted_index.world, | 4 |
| abstract_inverted_index.address | 43 |
| abstract_inverted_index.density | 103 |
| abstract_inverted_index.exploit | 93 |
| abstract_inverted_index.jointly | 119, 139 |
| abstract_inverted_index.machine | 6 |
| abstract_inverted_index.objects | 87 |
| abstract_inverted_index.person. | 115 |
| abstract_inverted_index.photos. | 52 |
| abstract_inverted_index.predict | 100 |
| abstract_inverted_index.propose | 54 |
| abstract_inverted_index.trained | 140 |
| abstract_inverted_index.(V-COCO) | 157 |
| abstract_inverted_index.HICO-DET | 159 |
| abstract_inverted_index.approach | 149 |
| abstract_inverted_index.detected | 114 |
| abstract_inverted_index.everyday | 51 |
| abstract_inverted_index.objects, | 125 |
| abstract_inverted_index.powerful | 82 |
| abstract_inverted_index.problem. | 38 |
| abstract_inverted_index.recently | 152 |
| abstract_inverted_index.results. | 166 |
| abstract_inverted_index.triplets | 48, 135 |
| abstract_inverted_index.validate | 147 |
| abstract_inverted_index.approach. | 64 |
| abstract_inverted_index.clothing, | 77 |
| abstract_inverted_index.datasets, | 160 |
| abstract_inverted_index.detecting | 29, 47 |
| abstract_inverted_index.important | 34 |
| abstract_inverted_index.instances | 13 |
| abstract_inverted_index.interact. | 18 |
| abstract_inverted_index.locations | 107 |
| abstract_inverted_index.practical | 35 |
| abstract_inverted_index.recognize | 10 |
| abstract_inverted_index.appearance | 70, 111 |
| abstract_inverted_index.compelling | 165 |
| abstract_inverted_index.end-to-end | 141 |
| abstract_inverted_index.hypothesis | 66 |
| abstract_inverted_index.individual | 11 |
| abstract_inverted_index.introduced | 153 |
| abstract_inverted_index.localizing | 85 |
| abstract_inverted_index.scientific | 37 |
| abstract_inverted_index.understand | 1 |
| abstract_inverted_index.challenging | 50 |
| abstract_inverted_index.efficiently | 132 |
| abstract_inverted_index.interacting | 90 |
| abstract_inverted_index.interaction | 134 |
| abstract_inverted_index.predictions | 130 |
| abstract_inverted_index.InteractNet. | 145 |
| abstract_inverted_index.human-object | 30 |
| abstract_inverted_index.interactions | 27, 31 |
| abstract_inverted_index.human-centric | 63 |
| abstract_inverted_index.quantitatively | 164 |
| abstract_inverted_index.action-specific | 102 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/8 |
| sustainable_development_goals[0].score | 0.41999998688697815 |
| sustainable_development_goals[0].display_name | Decent work and economic growth |
| citation_normalized_percentile |