MachMap: End-to-End Vectorized Solution for Compact HD-Map Construction Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2306.10301
This report introduces the 1st place winning solution for the Autonomous Driving Challenge 2023 - Online HD-map Construction. By delving into the vectorization pipeline, we elaborate an effective architecture, termed as MachMap, which formulates the task of HD-map construction as the point detection paradigm in the bird-eye-view space with an end-to-end manner. Firstly, we introduce a novel map-compaction scheme into our framework, leading to reducing the number of vectorized points by 93% without any expression performance degradation. Build upon the above process, we then follow the general query-based paradigm and propose a strong baseline with integrating a powerful CNN-based backbone like InternImage, a temporal-based instance decoder and a well-designed point-mask coupling head. Additionally, an extra optional ensemble stage is utilized to refine model predictions for better performance. Our MachMap-tiny with IN-1K initialization achieves a mAP of 79.1 on the Argoverse2 benchmark and the further improved MachMap-huge reaches the best mAP of 83.5, outperforming all the other online HD-map construction approaches on the final leaderboard with a distinct performance margin (> 9.8 mAP at least).
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2306.10301
- https://arxiv.org/pdf/2306.10301
- OA Status
- green
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4381551245
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4381551245Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2306.10301Digital Object Identifier
- Title
-
MachMap: End-to-End Vectorized Solution for Compact HD-Map ConstructionWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-06-17Full publication date if available
- Authors
-
Limeng Qiao, Yongchao Zheng, Peng Zhang, Wenjie Ding, Xi Qiu, Wei Xing, Chi ZhangList of authors in order
- Landing page
-
https://arxiv.org/abs/2306.10301Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2306.10301Direct 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/2306.10301Direct OA link when available
- Concepts
-
Computer science, Pipeline (software), Initialization, Benchmark (surveying), End-to-end principle, Process (computing), Margin (machine learning), Task (project management), Point (geometry), Vectorization (mathematics), Artificial intelligence, Real-time computing, Parallel computing, Machine learning, Cartography, Mathematics, Geography, Programming language, Economics, Operating system, Geometry, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.upon | 78 |
| abstract_inverted_index.with | 48, 94, 129, 164 |
| abstract_inverted_index.(> | 169 |
| abstract_inverted_index.83.5, | 151 |
| abstract_inverted_index.Build | 77 |
| abstract_inverted_index.IN-1K | 130 |
| abstract_inverted_index.above | 80 |
| abstract_inverted_index.extra | 114 |
| abstract_inverted_index.final | 162 |
| abstract_inverted_index.head. | 111 |
| abstract_inverted_index.model | 122 |
| abstract_inverted_index.novel | 56 |
| abstract_inverted_index.other | 155 |
| abstract_inverted_index.place | 5 |
| abstract_inverted_index.point | 41 |
| abstract_inverted_index.space | 47 |
| abstract_inverted_index.stage | 117 |
| abstract_inverted_index.which | 32 |
| abstract_inverted_index.HD-map | 16, 37, 157 |
| abstract_inverted_index.Online | 15 |
| abstract_inverted_index.better | 125 |
| abstract_inverted_index.follow | 84 |
| abstract_inverted_index.margin | 168 |
| abstract_inverted_index.number | 66 |
| abstract_inverted_index.online | 156 |
| abstract_inverted_index.points | 69 |
| abstract_inverted_index.refine | 121 |
| abstract_inverted_index.report | 1 |
| abstract_inverted_index.scheme | 58 |
| abstract_inverted_index.strong | 92 |
| abstract_inverted_index.termed | 29 |
| abstract_inverted_index.Driving | 11 |
| abstract_inverted_index.decoder | 105 |
| abstract_inverted_index.delving | 19 |
| abstract_inverted_index.further | 143 |
| abstract_inverted_index.general | 86 |
| abstract_inverted_index.leading | 62 |
| abstract_inverted_index.least). | 173 |
| abstract_inverted_index.manner. | 51 |
| abstract_inverted_index.propose | 90 |
| abstract_inverted_index.reaches | 146 |
| abstract_inverted_index.winning | 6 |
| abstract_inverted_index.without | 72 |
| abstract_inverted_index.Firstly, | 52 |
| abstract_inverted_index.MachMap, | 31 |
| abstract_inverted_index.achieves | 132 |
| abstract_inverted_index.backbone | 99 |
| abstract_inverted_index.baseline | 93 |
| abstract_inverted_index.coupling | 110 |
| abstract_inverted_index.distinct | 166 |
| abstract_inverted_index.ensemble | 116 |
| abstract_inverted_index.improved | 144 |
| abstract_inverted_index.instance | 104 |
| abstract_inverted_index.optional | 115 |
| abstract_inverted_index.paradigm | 43, 88 |
| abstract_inverted_index.powerful | 97 |
| abstract_inverted_index.process, | 81 |
| abstract_inverted_index.reducing | 64 |
| abstract_inverted_index.solution | 7 |
| abstract_inverted_index.utilized | 119 |
| abstract_inverted_index.CNN-based | 98 |
| abstract_inverted_index.Challenge | 12 |
| abstract_inverted_index.benchmark | 140 |
| abstract_inverted_index.detection | 42 |
| abstract_inverted_index.effective | 27 |
| abstract_inverted_index.elaborate | 25 |
| abstract_inverted_index.introduce | 54 |
| abstract_inverted_index.pipeline, | 23 |
| abstract_inverted_index.Argoverse2 | 139 |
| abstract_inverted_index.Autonomous | 10 |
| abstract_inverted_index.approaches | 159 |
| abstract_inverted_index.end-to-end | 50 |
| abstract_inverted_index.expression | 74 |
| abstract_inverted_index.formulates | 33 |
| abstract_inverted_index.framework, | 61 |
| abstract_inverted_index.introduces | 2 |
| abstract_inverted_index.point-mask | 109 |
| abstract_inverted_index.vectorized | 68 |
| abstract_inverted_index.integrating | 95 |
| abstract_inverted_index.leaderboard | 163 |
| abstract_inverted_index.performance | 75, 167 |
| abstract_inverted_index.predictions | 123 |
| abstract_inverted_index.query-based | 87 |
| abstract_inverted_index.InternImage, | 101 |
| abstract_inverted_index.MachMap-huge | 145 |
| abstract_inverted_index.MachMap-tiny | 128 |
| abstract_inverted_index.construction | 38, 158 |
| abstract_inverted_index.degradation. | 76 |
| abstract_inverted_index.performance. | 126 |
| abstract_inverted_index.Additionally, | 112 |
| abstract_inverted_index.Construction. | 17 |
| abstract_inverted_index.architecture, | 28 |
| abstract_inverted_index.bird-eye-view | 46 |
| abstract_inverted_index.outperforming | 152 |
| abstract_inverted_index.vectorization | 22 |
| abstract_inverted_index.well-designed | 108 |
| abstract_inverted_index.initialization | 131 |
| abstract_inverted_index.map-compaction | 57 |
| abstract_inverted_index.temporal-based | 103 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile |