mlsanityData to 7 Oct 2026

Polymap: generating high definition map based on rasterized polygons

arXiv 2511.05944 ↗First posted 8 Nov 2025cs.CVcited by 0

Not on the map. Why?

Abstract (arXiv)

The perception of high-definition maps is an integral component of environmental perception in autonomous driving systems. Existing research have often focused on online construction of high-definition maps. For instance, the Maptr[9] series employ a detection-based method to output vectorized map instances parallelly in an end-to-end manner. However, despite their capability for real-time construction, detection-based methods are observed to lack robust generalizability[19], which hampers their applicability in auto-labeling systems. Therefore, aiming to improve the generalizability, we reinterpret road elements as rasterized polygons and design a concise framework based on instance segmentation. Initially, a segmentation-based transformer is employed to deliver instance masks in an end-to-end manner; succeeding this step, a Potrace-based[17] post-processing module is used to ultimately yield vectorized map elements. Quantitative results attained on the Nuscene[1] dataset substantiate the effectiveness and generaliz-ability of our method.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 20 of its 22 references that are in the map. First posted on arXiv 8 Nov 2025.

Builds on

20 of 22 references.

References · 20

  1. 2019nuScenes: A multimodal dataset for autonomous drivingcited by 4,485
  2. 2021Masked-attention Mask Transformer for Universal Image Segmentationcited by 2,338
  3. 2022BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformerscited by 1,213
  4. 2020Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3Dcited by 1,040
  5. 2022MapTR: Structured Modeling and Learning for Online Vectorized HD Map Constructioncited by 311
  6. 2021HDMapNet: An Online HD Map Construction and Evaluation Frameworkcited by 280
  7. 2022Cross-view Transformers for real-time Map-view Semantic Segmentationcited by 264
  8. 2022VectorMapNet: End-to-end Vectorized HD Map Learningcited by 243
  9. 2023MapTRv2: An End-to-End Framework for Online Vectorized HD Map Constructioncited by 192
  10. 2017Spatial As Deep: Spatial CNN for Traffic Scene Understandingcited by 187
  11. 2019Cross-view Semantic Segmentation for Sensing Surroundingscited by 173
  12. 2023StreamMapNet: Streaming Mapping Network for Vectorized Online HD Map Constructioncited by 143
8 more
  1. 2018Towards End-to-End Lane Detection: an Instance Segmentation Approachcited by 129
  2. 2023PivotNet: Vectorized Pivot Learning for End-to-end HD Map Constructioncited by 84
  3. 2022Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformercited by 80
  4. 2023End-to-End Vectorized HD-map Construction with Piecewise Bezier Curvecited by 80
  5. 2020RESA: Recurrent Feature-Shift Aggregator for Lane Detectioncited by 77
  6. 2024MapTracker: Tracking with Strided Memory Fusion for Consistent Vector HD Mappingcited by 67
  7. 2023Online Map Vectorization for Autonomous Driving: A Rasterization Perspectivecited by 54
  8. 2018LaneNet: Real-Time Lane Detection Networks for Autonomous Drivingcited by 39

Built on by

Not cited yet.