Temporal Early Exits for Efficient Video Object Detection Article Swipe
Amin Sabet
,
Jonathon Hare
,
Bashir M. Al‐Hashimi
,
Geoff V. Merrett
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2106.11208
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2106.11208
Transferring image-based object detectors to the domain of video remains challenging under resource constraints. Previous efforts utilised optical flow to allow unchanged features to be propagated, however, the overhead is considerable when working with very slowly changing scenes from applications such as surveillance. In this paper, we propose temporal early exits to reduce the computational complexity of per-frame video object detection. Multiple temporal early exit modules with low computational overhead are inserted at early layers of the backbone network to identify the semantic differences between consecutive frames. Full computation is only required if the frame is identified as having a semantic change to previous frames; otherwise, detection results from previous frames are reused. Experiments on CDnet show that our method significantly reduces the computational complexity and execution of per-frame video object detection up to $34 \times$ compared to existing methods with an acceptable reduction of 2.2\% in mAP.
Related Topics
Concepts
Computer science
Frame (networking)
Overhead (engineering)
Computational complexity theory
Object (grammar)
Object detection
Computer vision
Computation
Reduction (mathematics)
Artificial intelligence
Domain (mathematical analysis)
Detector
Real-time computing
Frame rate
Pattern recognition (psychology)
Algorithm
Computer network
Mathematics
Mathematical analysis
Operating system
Telecommunications
Geometry
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2106.11208
- https://arxiv.org/pdf/2106.11208
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4287115843
All OpenAlex metadata
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https://openalex.org/W4287115843Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2106.11208Digital Object Identifier
- Title
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Temporal Early Exits for Efficient Video Object DetectionWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2021Year of publication
- Publication date
-
2021-06-21Full publication date if available
- Authors
-
Amin Sabet, Jonathon Hare, Bashir M. Al‐Hashimi, Geoff V. MerrettList of authors in order
- Landing page
-
https://arxiv.org/abs/2106.11208Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2106.11208Direct 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/2106.11208Direct OA link when available
- Concepts
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Computer science, Frame (networking), Overhead (engineering), Computational complexity theory, Object (grammar), Object detection, Computer vision, Computation, Reduction (mathematics), Artificial intelligence, Domain (mathematical analysis), Detector, Real-time computing, Frame rate, Pattern recognition (psychology), Algorithm, Computer network, Mathematics, Mathematical analysis, Operating system, Telecommunications, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.paper, | 45 |
| abstract_inverted_index.reduce | 52 |
| abstract_inverted_index.scenes | 37 |
| abstract_inverted_index.slowly | 35 |
| abstract_inverted_index.\times$ | 135 |
| abstract_inverted_index.between | 84 |
| abstract_inverted_index.efforts | 15 |
| abstract_inverted_index.frames. | 86 |
| abstract_inverted_index.frames; | 104 |
| abstract_inverted_index.methods | 139 |
| abstract_inverted_index.modules | 65 |
| abstract_inverted_index.network | 78 |
| abstract_inverted_index.optical | 17 |
| abstract_inverted_index.propose | 47 |
| abstract_inverted_index.reduces | 121 |
| abstract_inverted_index.remains | 9 |
| abstract_inverted_index.results | 107 |
| abstract_inverted_index.reused. | 112 |
| abstract_inverted_index.working | 32 |
| abstract_inverted_index.Multiple | 61 |
| abstract_inverted_index.Previous | 14 |
| abstract_inverted_index.backbone | 77 |
| abstract_inverted_index.changing | 36 |
| abstract_inverted_index.compared | 136 |
| abstract_inverted_index.existing | 138 |
| abstract_inverted_index.features | 22 |
| abstract_inverted_index.however, | 26 |
| abstract_inverted_index.identify | 80 |
| abstract_inverted_index.inserted | 71 |
| abstract_inverted_index.overhead | 28, 69 |
| abstract_inverted_index.previous | 103, 109 |
| abstract_inverted_index.required | 91 |
| abstract_inverted_index.resource | 12 |
| abstract_inverted_index.semantic | 82, 100 |
| abstract_inverted_index.temporal | 48, 62 |
| abstract_inverted_index.utilised | 16 |
| abstract_inverted_index.detection | 106, 131 |
| abstract_inverted_index.detectors | 3 |
| abstract_inverted_index.execution | 126 |
| abstract_inverted_index.per-frame | 57, 128 |
| abstract_inverted_index.reduction | 143 |
| abstract_inverted_index.unchanged | 21 |
| abstract_inverted_index.acceptable | 142 |
| abstract_inverted_index.complexity | 55, 124 |
| abstract_inverted_index.detection. | 60 |
| abstract_inverted_index.identified | 96 |
| abstract_inverted_index.otherwise, | 105 |
| abstract_inverted_index.Experiments | 113 |
| abstract_inverted_index.challenging | 10 |
| abstract_inverted_index.computation | 88 |
| abstract_inverted_index.consecutive | 85 |
| abstract_inverted_index.differences | 83 |
| abstract_inverted_index.image-based | 1 |
| abstract_inverted_index.propagated, | 25 |
| abstract_inverted_index.Transferring | 0 |
| abstract_inverted_index.applications | 39 |
| abstract_inverted_index.considerable | 30 |
| abstract_inverted_index.constraints. | 13 |
| abstract_inverted_index.computational | 54, 68, 123 |
| abstract_inverted_index.significantly | 120 |
| abstract_inverted_index.surveillance. | 42 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| 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 |