mlsanityData to 7 Oct 2026

MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

arXiv 2208.14437 ↗First posted 30 Aug 2022cs.CV cs.ROcited by 311

Not on the map. Why?

Cited by 75 in End-to-end autonomous driving, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

High-definition (HD) map provides abundant and precise environmental information of the driving scene, serving as a fundamental and indispensable component for planning in autonomous driving system. We present MapTR, a structured end-to-end Transformer for efficient online vectorized HD map construction. We propose a unified permutation-equivalent modeling approach, i.e., modeling map element as a point set with a group of equivalent permutations, which accurately describes the shape of map element and stabilizes the learning process. We design a hierarchical query embedding scheme to flexibly encode structured map information and perform hierarchical bipartite matching for map element learning. MapTR achieves the best performance and efficiency with only camera input among existing vectorized map construction approaches on nuScenes dataset. In particular, MapTR-nano runs at real-time inference speed (25.1 FPS) on RTX 3090, 8× faster than the existing state-of-the-art camera-based method while achieving 5.0 higher mAP. Even compared with the existing state-of-the-art multi-modality method, MapTR-nano achieves 0.7 higher mAP, and MapTR-tiny achieves 13.5 higher mAP and 3× faster inference speed. Abundant qualitative results show that MapTR maintains stable and robust map construction quality in complex and various driving scenes. MapTR is of great application value in autonomous driving. Code and more demos are available at urlhttps://github.com/hustvl/MapTR.

Key facts. Cited by 311 papers in the map (data through 7 Oct 2026). Builds on 33 of its 44 references that are in the map. First posted on arXiv 30 Aug 2022.

Builds on

33 of 44 references.

References · 33

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
  3. 2020End-to-End Object Detection with Transformerscited by 7,384
  4. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,415
  5. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  6. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,410
  7. 2018PointPillars: Fast Encoders for Object Detection from Point Cloudscited by 1,707
  8. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  9. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,040
  10. 2022BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representationcited by 844
  11. 2021BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-Viewcited by 711
  12. 2022BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detectioncited by 568
21 more
  1. 2021HDMapNet: An Online HD Map Construction and Evaluation Frameworkcited by 280
  2. 2022Cross-view Transformers for real-time Map-view Semantic Segmentationcited by 264
  3. 2022VectorMapNet: End-to-end Vectorized HD Map Learningcited by 243
  4. 2019PolarMask: Single Shot Instance Segmentation with Polar Representationcited by 188
  5. 2020LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mappingcited by 185
  6. 2021You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detectioncited by 170
  7. 2022PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmarkcited by 140
  8. 2020Keep your Eyes on the Lane: Real-time Attention-guided Lane Detectioncited by 137
  9. 2022Vision-Centric BEV Perception: A Surveycited by 126
  10. 2020Deep Snake for Real-Time Instance Segmentationcited by 111
  11. 2020End-to-end Lane Shape Prediction with Transformerscited by 111
  12. 20183D-LaneNet: End-to-End 3D Multiple Lane Detectioncited by 106
  13. 2021Structured Bird's-Eye-View Traffic Scene Understanding from Onboard Imagescited by 98
  14. 2019Fast Interactive Object Annotation with Curve-GCNcited by 95
  15. 2019PolyTransform: Deep Polygon Transformer for Instance Segmentationcited by 92
  16. 2022Rethinking Efficient Lane Detection via Curve Modelingcited by 87
  17. 2022Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformercited by 80
  18. 2022A Keypoint-based Global Association Network for Lane Detectioncited by 68
  19. 2019Explicit Shape Encoding for Real-Time Instance Segmentationcited by 41
  20. 2022Vision-based Uneven BEV Representation Learning with Polar Rasterization and Surface Estimationcited by 23
  21. 2022SharpContour: A Contour-based Boundary Refinement Approach for Efficient and Accurate Instance Segmentationcited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 47; 2024: 100; 2025: 105; 2026: 58.

311 papers.

Sort:

By area:

  1. 2023VAD: Vectorized Scene Representation for Efficient Autonomous Drivingcited by 613
  2. 2023End-to-end Autonomous Driving: Challenges and Frontierscited by 485
  3. 2024Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllabilitycited by 337
  4. 2024DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Drivingcited by 324
  5. 2023Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Drivingcited by 309
  6. 2024VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planningcited by 287
  7. 2023Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?cited by 242
  8. 2024SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representationcited by 239
  9. 2023OccWorld: Learning a 3D Occupancy World Model for Autonomous Drivingcited by 230
  10. 2024EMMA: End-to-End Multimodal Model for Autonomous Drivingcited by 226
  11. 2024GenAD: Generative End-to-End Autonomous Drivingcited by 225
  12. 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 192
38 more
  1. 2023Panacea: Panoramic and Controllable Video Generation for Autonomous Drivingcited by 165
  2. 2024Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Drivingcited by 156
  3. 2023StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Constructioncited by 143
  4. 2025DriveTransformer: Unified Transformer for Scalable End-to-End Autonomous Drivingcited by 125
  5. 2023PanoOcc: Unified Occupancy Representation for Camera-based 3D Panoptic Segmentationcited by 114
  6. 2024Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agentscited by 91
  7. 2025World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Modelcited by 91
  8. 2023PivotNet: Vectorized Pivot Learning for End-to-end HD Map Constructioncited by 84
  9. 2023OpenLane-V2: A Topology Reasoning Benchmark for Unified 3D HD Mappingcited by 83
  10. 2025RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learningcited by 76
  11. 2023Sparse4D v3: Advancing End-to-End 3D Detection and Trackingcited by 69
  12. 2023Neural Map Prior for Autonomous Drivingcited by 68
  13. 2024MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mappingcited by 67
  14. 2023Fully Sparse 3D Occupancy Predictioncited by 61
  15. 2023Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Mapscited by 58
  16. 2023LaneSegNet: Map Learning with Lane Segment Perception for Autonomous Drivingcited by 57
  17. 2023Online Map Vectorization for Autonomous Driving: A Rasterization Perspectivecited by 54
  18. 2024P-MapNet: Far-seeing Map Generator Enhanced by both SDMap and HDMap Priorscited by 54
  19. 2023Graph-based Topology Reasoning for Driving Scenescited by 53
  20. 2024MGMap: Mask-Guided Learning for Online Vectorized HD Map Constructioncited by 52
  21. 2025DiffusionDriveV2: Reinforcement Learning-Constrained Truncated Diffusion Modeling in End-to-End Autonomous Drivingcited by 52
  22. 2023Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Constructioncited by 50
  23. 2024HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Constructioncited by 48
  24. 2024Leveraging Enhanced Queries of Point Sets for Vectorized Map Constructioncited by 46
  25. 2024SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Drivingcited by 46
  26. 2024Navigation-Guided Sparse Scene Representation for End-to-End Autonomous Drivingcited by 46
  27. 2023Localization Is All You Evaluate: Data Leakage in Online Mapping Datasets and How to Fix Itcited by 44
  28. 2024Stream Query Denoising for Vectorized HD Map Constructioncited by 43
  29. 2025DriveLaW:Unifying Planning and Video Generation in a Latent Driving Worldcited by 43
  30. 2023Online Vectorized HD Map Construction using Geometrycited by 42
  31. 2025ReSim: Reliable World Simulation for Autonomous Drivingcited by 42
  32. 2023TopoMLP: A Simple yet Strong Pipeline for Driving Topology Reasoningcited by 41
  33. 2024Solving Motion Planning Tasks with a Scalable Generative Modelcited by 40
  34. 2023PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Modelscited by 36
  35. 2024ViewFormer: Exploring Spatiotemporal Modeling for Multi-View 3D Occupancy Perception via View-Guided Transformerscited by 36
  36. 2024T2SG: Traffic Topology Scene Graph for Topology Reasoning in Autonomous Drivingcited by 35
  37. 2025HiP-AD: Hierarchical and Multi-Granularity Planning with Deformable Attention for Autonomous Driving in a Single Decodercited by 35
  38. 2023PPAD: Iterative Interactions of Prediction and Planning for End-to-end Autonomous Drivingcited by 33

50 most cited of 311 All 311 (JSON)