CenterNet: Keypoint Triplets for Object Detection Article Swipe
Kaiwen Duan
,
Song Bai
,
Lingxi Xie
,
Honggang Qi
,
Qingming Huang
,
Qi Tian
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1904.08189
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1904.08189
In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regions. This paper presents an efficient solution which explores the visual patterns within each cropped region with minimal costs. We build our framework upon a representative one-stage keypoint-based detector named CornerNet. Our approach, named CenterNet, detects each object as a triplet, rather than a pair, of keypoints, which improves both precision and recall. Accordingly, we design two customized modules named cascade corner pooling and center pooling, which play the roles of enriching information collected by both top-left and bottom-right corners and providing more recognizable information at the central regions, respectively. On the MS-COCO dataset, CenterNet achieves an AP of 47.0%, which outperforms all existing one-stage detectors by at least 4.9%. Meanwhile, with a faster inference speed, CenterNet demonstrates quite comparable performance to the top-ranked two-stage detectors. Code is available at https://github.com/Duankaiwen/CenterNet.
Related Topics
Concepts
Pooling
Computer science
Bounding overwatch
Object (grammar)
Detector
Code (set theory)
Inference
Object detection
Cascade
Artificial intelligence
Precision and recall
Pattern recognition (psychology)
Computer vision
Engineering
Programming language
Set (abstract data type)
Telecommunications
Chemical engineering
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1904.08189
- https://arxiv.org/pdf/1904.08189
- OA Status
- green
- Cited By
- 158
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2936525159
All OpenAlex metadata
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https://openalex.org/W2936525159Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.1904.08189Digital Object Identifier
- Title
-
CenterNet: Keypoint Triplets for Object DetectionWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-04-17Full publication date if available
- Authors
-
Kaiwen Duan, Song Bai, Lingxi Xie, Honggang Qi, Qingming Huang, Qi TianList of authors in order
- Landing page
-
https://arxiv.org/abs/1904.08189Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1904.08189Direct link to full text PDF
- Open access
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/1904.08189Direct OA link when available
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Pooling, Computer science, Bounding overwatch, Object (grammar), Detector, Code (set theory), Inference, Object detection, Cascade, Artificial intelligence, Precision and recall, Pattern recognition (psychology), Computer vision, Engineering, Programming language, Set (abstract data type), Telecommunications, Chemical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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158Total citation count in OpenAlex
- Citations by year (recent)
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2025: 5, 2024: 13, 2023: 12, 2022: 10, 2021: 56Per-year citation counts (last 5 years)
- References (count)
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45Number 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.We | 46 |
| abstract_inverted_index.an | 21, 31, 123 |
| abstract_inverted_index.as | 65 |
| abstract_inverted_index.at | 112, 134, 156 |
| abstract_inverted_index.by | 101, 133 |
| abstract_inverted_index.is | 154 |
| abstract_inverted_index.of | 10, 20, 72, 97, 125 |
| abstract_inverted_index.to | 17, 148 |
| abstract_inverted_index.we | 81 |
| abstract_inverted_index.Our | 58 |
| abstract_inverted_index.all | 129 |
| abstract_inverted_index.and | 78, 90, 104, 107 |
| abstract_inverted_index.due | 16 |
| abstract_inverted_index.our | 48 |
| abstract_inverted_index.the | 18, 25, 36, 95, 113, 118, 149 |
| abstract_inverted_index.two | 83 |
| abstract_inverted_index.Code | 153 |
| abstract_inverted_index.This | 28 |
| abstract_inverted_index.both | 76, 102 |
| abstract_inverted_index.each | 40, 63 |
| abstract_inverted_index.into | 24 |
| abstract_inverted_index.lack | 19 |
| abstract_inverted_index.look | 23 |
| abstract_inverted_index.more | 109 |
| abstract_inverted_index.play | 94 |
| abstract_inverted_index.than | 69 |
| abstract_inverted_index.upon | 50 |
| abstract_inverted_index.with | 43, 138 |
| abstract_inverted_index.4.9%. | 136 |
| abstract_inverted_index.build | 47 |
| abstract_inverted_index.large | 8 |
| abstract_inverted_index.least | 135 |
| abstract_inverted_index.named | 56, 60, 86 |
| abstract_inverted_index.often | 5 |
| abstract_inverted_index.pair, | 71 |
| abstract_inverted_index.paper | 29 |
| abstract_inverted_index.quite | 145 |
| abstract_inverted_index.roles | 96 |
| abstract_inverted_index.which | 34, 74, 93, 127 |
| abstract_inverted_index.47.0%, | 126 |
| abstract_inverted_index.boxes, | 14 |
| abstract_inverted_index.center | 91 |
| abstract_inverted_index.corner | 88 |
| abstract_inverted_index.costs. | 45 |
| abstract_inverted_index.design | 82 |
| abstract_inverted_index.faster | 140 |
| abstract_inverted_index.number | 9 |
| abstract_inverted_index.object | 1, 12, 64 |
| abstract_inverted_index.rather | 68 |
| abstract_inverted_index.region | 42 |
| abstract_inverted_index.speed, | 142 |
| abstract_inverted_index.suffer | 6 |
| abstract_inverted_index.visual | 37 |
| abstract_inverted_index.within | 39 |
| abstract_inverted_index.MS-COCO | 119 |
| abstract_inverted_index.cascade | 87 |
| abstract_inverted_index.central | 114 |
| abstract_inverted_index.corners | 106 |
| abstract_inverted_index.cropped | 26, 41 |
| abstract_inverted_index.detects | 62 |
| abstract_inverted_index.minimal | 44 |
| abstract_inverted_index.modules | 85 |
| abstract_inverted_index.pooling | 89 |
| abstract_inverted_index.recall. | 79 |
| abstract_inverted_index.achieves | 122 |
| abstract_inverted_index.arguably | 15 |
| abstract_inverted_index.bounding | 13 |
| abstract_inverted_index.dataset, | 120 |
| abstract_inverted_index.detector | 55 |
| abstract_inverted_index.existing | 130 |
| abstract_inverted_index.explores | 35 |
| abstract_inverted_index.improves | 75 |
| abstract_inverted_index.patterns | 38 |
| abstract_inverted_index.pooling, | 92 |
| abstract_inverted_index.presents | 30 |
| abstract_inverted_index.regions, | 115 |
| abstract_inverted_index.regions. | 27 |
| abstract_inverted_index.solution | 33 |
| abstract_inverted_index.top-left | 103 |
| abstract_inverted_index.triplet, | 67 |
| abstract_inverted_index.CenterNet | 121, 143 |
| abstract_inverted_index.approach, | 59 |
| abstract_inverted_index.available | 155 |
| abstract_inverted_index.collected | 100 |
| abstract_inverted_index.detectors | 132 |
| abstract_inverted_index.efficient | 32 |
| abstract_inverted_index.enriching | 98 |
| abstract_inverted_index.framework | 49 |
| abstract_inverted_index.incorrect | 11 |
| abstract_inverted_index.inference | 141 |
| abstract_inverted_index.one-stage | 53, 131 |
| abstract_inverted_index.precision | 77 |
| abstract_inverted_index.providing | 108 |
| abstract_inverted_index.two-stage | 151 |
| abstract_inverted_index.CenterNet, | 61 |
| abstract_inverted_index.CornerNet. | 57 |
| abstract_inverted_index.Meanwhile, | 137 |
| abstract_inverted_index.additional | 22 |
| abstract_inverted_index.approaches | 4 |
| abstract_inverted_index.comparable | 146 |
| abstract_inverted_index.customized | 84 |
| abstract_inverted_index.detection, | 2 |
| abstract_inverted_index.detectors. | 152 |
| abstract_inverted_index.keypoints, | 73 |
| abstract_inverted_index.top-ranked | 150 |
| abstract_inverted_index.information | 99, 111 |
| abstract_inverted_index.outperforms | 128 |
| abstract_inverted_index.performance | 147 |
| abstract_inverted_index.Accordingly, | 80 |
| abstract_inverted_index.bottom-right | 105 |
| abstract_inverted_index.demonstrates | 144 |
| abstract_inverted_index.recognizable | 110 |
| abstract_inverted_index.respectively. | 116 |
| abstract_inverted_index.keypoint-based | 3, 54 |
| abstract_inverted_index.representative | 52 |
| abstract_inverted_index.https://github.com/Duankaiwen/CenterNet. | 157 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |