Rethinking IoU-based Optimization for Single-stage 3D Object Detection Article Swipe
Hualian Sheng
,
Sijia Cai
,
Na Zhao
,
Bing Deng
,
Jianqiang Huang
,
Xian-Sheng Hua
,
Minjian Zhao
,
Gim Hee Lee
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.09332
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2207.09332
Since Intersection-over-Union (IoU) based optimization maintains the consistency of the final IoU prediction metric and losses, it has been widely used in both regression and classification branches of single-stage 2D object detectors. Recently, several 3D object detection methods adopt IoU-based optimization and directly replace the 2D IoU with 3D IoU. However, such a direct computation in 3D is very costly due to the complex implementation and inefficient backward operations. Moreover, 3D IoU-based optimization is sub-optimal as it is sensitive to rotation and thus can cause training instability and detection performance deterioration. In this paper, we propose a novel Rotation-Decoupled IoU (RDIoU) method that can mitigate the rotation-sensitivity issue, and produce more efficient optimization objectives compared with 3D IoU during the training stage. Specifically, our RDIoU simplifies the complex interactions of regression parameters by decoupling the rotation variable as an independent term, yet preserving the geometry of 3D IoU. By incorporating RDIoU into both the regression and classification branches, the network is encouraged to learn more precise bounding boxes and concurrently overcome the misalignment issue between classification and regression. Extensive experiments on the benchmark KITTI and Waymo Open Dataset validate that our RDIoU method can bring substantial improvement for the single-stage 3D object detection.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2207.09332
- https://arxiv.org/pdf/2207.09332
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4286588391
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4286588391Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2207.09332Digital Object Identifier
- Title
-
Rethinking IoU-based Optimization for Single-stage 3D Object DetectionWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-07-19Full publication date if available
- Authors
-
Hualian Sheng, Sijia Cai, Na Zhao, Bing Deng, Jianqiang Huang, Xian-Sheng Hua, Minjian Zhao, Gim Hee LeeList of authors in order
- Landing page
-
https://arxiv.org/abs/2207.09332Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2207.09332Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2207.09332Direct OA link when available
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Computer science, Benchmark (surveying), Artificial intelligence, Object detection, Bounding overwatch, Metric (unit), Pattern recognition (psychology), Engineering, Operations management, Geodesy, GeographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2023: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.independent | 139 |
| abstract_inverted_index.inefficient | 66 |
| abstract_inverted_index.instability | 86 |
| abstract_inverted_index.operations. | 68 |
| abstract_inverted_index.performance | 89 |
| abstract_inverted_index.regression. | 177 |
| abstract_inverted_index.sub-optimal | 74 |
| abstract_inverted_index.substantial | 195 |
| abstract_inverted_index.concurrently | 169 |
| abstract_inverted_index.interactions | 128 |
| abstract_inverted_index.misalignment | 172 |
| abstract_inverted_index.optimization | 4, 40, 72, 112 |
| abstract_inverted_index.single-stage | 28, 199 |
| abstract_inverted_index.Specifically, | 122 |
| abstract_inverted_index.incorporating | 149 |
| abstract_inverted_index.classification | 25, 156, 175 |
| abstract_inverted_index.deterioration. | 90 |
| abstract_inverted_index.implementation | 64 |
| abstract_inverted_index.Rotation-Decoupled | 98 |
| abstract_inverted_index.rotation-sensitivity | 106 |
| abstract_inverted_index.Intersection-over-Union | 1 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile |