mlsanityData to 14 Oct 2026

VectorMapNet: End-to-end Vectorized HD Map Learning

arXiv 2206.08920 ↗First posted 17 Jun 2022cs.CV cs.ROcited by 245

Not on the map. Why?

Cited by 46 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Autonomous driving systems require High-Definition (HD) semantic maps to navigate around urban roads. Existing solutions approach the semantic mapping problem by offline manual annotation, which suffers from serious scalability issues. Recent learning-based methods produce dense rasterized segmentation predictions to construct maps. However, these predictions do not include instance information of individual map elements and require heuristic post-processing to obtain vectorized maps. To tackle these challenges, we introduce an end-to-end vectorized HD map learning pipeline, termed VectorMapNet. VectorMapNet takes onboard sensor observations and predicts a sparse set of polylines in the bird's-eye view. This pipeline can explicitly model the spatial relation between map elements and generate vectorized maps that are friendly to downstream autonomous driving tasks. Extensive experiments show that VectorMapNet achieve strong map learning performance on both nuScenes and Argoverse2 dataset, surpassing previous state-of-the-art methods by 14.2 mAP and 14.6mAP. Qualitatively, VectorMapNet is capable of generating comprehensive maps and capturing fine-grained details of road geometry. To the best of our knowledge, VectorMapNet is the first work designed towards end-to-end vectorized map learning from onboard observations. Our project website is available at urlhttps://tsinghua-mars-lab.github.io/vectormapnet/.

Key facts. Cited by 245 papers in the map (data through 14 Oct 2026). Builds on 51 of its 71 references that are in the map. First posted on arXiv 17 Jun 2022.

Builds on

51 of 71 references.

References · 51

  1. 2017Attention Is All You Needcited by 60,361
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  3. 2020End-to-End Object Detection with Transformerscited by 7,414
  4. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  5. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,523
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  12. 2015Scheduled Sampling for Sequence Prediction with Recurrent Neural Networkscited by 803
38 more
  1. 2018Image Transformercited by 772
  2. 2019Argoverse: 3D Tracking and Forecasting with Rich Mapscited by 732
  3. 2021DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queriescited by 658
  4. 2020VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representationcited by 530
  5. 2022DN-DETR: Accelerate DETR Training by Introducing Query DeNoisingcited by 488
  6. 2020TNT: Target-driveN Trajectory Predictioncited by 347
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  10. 2021MP3: A Unified Model to Map, Perceive, Predict and Plancited by 212
  11. 2021Multimodal Motion Prediction with Stacked Transformerscited by 208
  12. 2022FUTR3D: A Unified Sensor Fusion Framework for 3D Detectioncited by 194
  13. 2017Spatial As Deep: Spatial CNN for Traffic Scene Understandingcited by 187
  14. 2020Predicting Semantic Map Representations from Images using Pyramid Occupancy Networkscited by 175
  15. 2019Cross-view Semantic Segmentation for Sensing Surroundingscited by 174
  16. 2019End-to-End Multi-View Fusion for 3D Object Detection in LiDAR Point Cloudscited by 171
  17. 2020DeepSVG: A Hierarchical Generative Network for Vector Graphics Animationcited by 159
  18. 2020Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representationscited by 153
  19. 2018Towards End-to-End Lane Detection: an Instance Segmentation Approachcited by 129
  20. 2020LGSVL Simulator: A High Fidelity Simulator for Autonomous Drivingcited by 121
  21. 2018Efficient Interactive Annotation of Segmentation Datasets with Polygon-RNN++cited by 120
  22. 2021Im2Vec: Synthesizing Vector Graphics without Vector Supervisioncited by 116
  23. 2021Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Imagescited by 98
  24. 2021CanvasVAE: Learning to Generate Vector Graphic Documentscited by 95
  25. 2019PolyTransform: Deep Polygon Transformer for Instance Segmentationcited by 92
  26. 2017Annotating Object Instances with a Polygon-RNNcited by 88
  27. 2022Rethinking Efficient Lane Detection via Curve Modelingcited by 88
  28. 2018Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networkscited by 84
  29. 2021Computer-Aided Design as Languagecited by 82
  30. 2020HDNET: Exploiting HD Maps for 3D Object Detectioncited by 78
  31. 2021Line Segment Detection Using Transformers without Edgescited by 73
  32. 2017VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognitioncited by 56
  33. 2021PolyWorld: Polygonal Building Extraction with Graph Neural Networks in Satellite Imagescited by 43
  34. 2021HDMapGen: A Hierarchical Graph Generative Model of High Definition Mapscited by 40
  35. 2020Hierarchical Recurrent Attention Networks for Structured Online Mapscited by 38
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  37. 2020Convolutional Recurrent Network for Road Boundary Extractioncited by 33
  38. 2016TorontoCity: Seeing the World with a Million Eyescited by 24

50 most cited of 51 All 51 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 5; 2023: 42; 2024: 77; 2025: 77; 2026: 44.

245 papers.

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  1. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 622
  2. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 334
  3. 2022MapTR: Structured Modeling and Learning for Online Vectorized HD Map Constructioncited by 314
  4. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 289
  5. 2023Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?cited by 242
  6. 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 241
  7. 2023OccWorld: Learning a 3D Occupancy World Model for Autonomous Drivingcited by 233
  8. 2024EMMA: End-to-End Multimodal Model for Autonomous Drivingcited by 231
  9. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  10. 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 193
  11. 2023StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Constructioncited by 145
  12. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 115
38 more
  1. 2023PivotNet: Vectorized Pivot Learning for End-to-end HD Map Constructioncited by 85
  2. 2023OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mappingcited by 83
  3. 2023Neural Map Prior for Autonomous Drivingcited by 68
  4. 2024MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mappingcited by 68
  5. 2023Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Mapscited by 58
  6. 2023LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Drivingcited by 57
  7. 2023Graph-based Topology Reasoning for Driving Scenescited by 54
  8. 2023Online Map Vectorization for Autonomous Driving: A Rasterization Perspectivecited by 54
  9. 2024P-MapNet: Far-seeing Map Generator Enhanced by both SDMap and HDMap Priorscited by 54
  10. 2024MGMap: Mask-Guided Learning for Online Vectorized HD Map Constructioncited by 52
  11. 2023Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Constructioncited by 50
  12. 2024HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Constructioncited by 48
  13. 2024SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Drivingcited by 47
  14. 2024Leveraging Enhanced Queries of Point Sets for Vectorized Map Constructioncited by 46
  15. 2024Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Drivingcited by 46
  16. 2023Localization Is All You Evaluate: Data Leakage in Online Mapping Datasets and How to Fix Itcited by 44
  17. 2024Stream Query Denoising for Vectorized HD Map Constructioncited by 43
  18. 2023Online Vectorized HD Map Construction using Geometrycited by 42
  19. 2023TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoningcited by 41
  20. 2023InstaGraM: Instance-level Graph Modeling for Vectorized HD Map Learningcited by 40
  21. 2024Solving Motion Planning Tasks with a Scalable Generative Modelcited by 40
  22. 2022SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generationcited by 39
  23. 2023PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Modelscited by 38
  24. 2024T2SG: Traffic Topology Scene Graph for Topology Reasoning in Autonomous Drivingcited by 35
  25. 2025HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decodercited by 35
  26. 2024Producing and Leveraging Online Map Uncertainty in Trajectory Predictioncited by 33
  27. 2024GaussianAD: Gaussian-Centric End-to-End Autonomous Drivingcited by 31
  28. 2023Data-driven Traffic Simulation: A Comprehensive Reviewcited by 29
  29. 2024TopoLogic: An Interpretable Pipeline for Lane Topology Reasoning on Driving Scenescited by 29
  30. 2024Enhancing Vectorized Map Perception with Historical Rasterized Mapscited by 29
  31. 2022Perceive, Interact, Predict: Learning Dynamic and Static Clues for End-to-End Motion Predictioncited by 28
  32. 2023Complementing Onboard Sensors with Satellite Map: A New Perspective for HD Map Constructioncited by 28
  33. 2024Segment Anything Model for Road Network Graph Extractioncited by 28
  34. 2024Is Your HD Map Constructor Reliable under Sensor Corruptions?cited by 28
  35. 2024MapDistill: Boosting Efficient Camera-based HD Map Construction via Camera-LiDAR Fusion Model Distillationcited by 26
  36. 2024Mask2Map: Vectorized HD Map Construction Using Bird's Eye View Segmentation Maskscited by 26
  37. 2025DiffAD: A Unified Diffusion Modeling Approach for Autonomous Drivingcited by 26
  38. 2023Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Reviewcited by 25

50 most cited of 245 All 245 (JSON)