├── LICENSE └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2024 LoveFaFa2333 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Awesome-Online-HDMap 2 | # Classified by timeline 3 | Methods of online HDmap for autonomous driving. Please note that the year classification is based on the published time on arxiv. 4 | ## 2025 5 | 1. **MapFusion**: A Novel BEV Feature Fusion Network for Multi-modal Map Construction. arXiv preprint arXiv:2502.04377 (2025). [[paper](https://www.arxiv.org/pdf/2502.04377)] 6 | 2. **Chameleon**: Fast-slow Neuro-symbolic Lane Topology Extraction. ICRA, 2025. [[paper](https://arxiv.org/pdf/2503.07485)] [[code](https://github.com/XR-Lee/neural-symbolic)] 7 | 3. **CleanMAP**: Distilling Multimodal LLMs for Confidence-Driven Crowdsourced HD Map Updates. CVPR WDFM-AD Workshop, 2025. [[paper](https://arxiv.org/pdf/2504.10738)] [[project page](https://ankit-zefan.github.io/CleanMap/)] 8 | 4. **SeqGrowGraph**: Learning Lane Topology as a Chain of Graph Expansions. ICCV, 2025. [[paper](https://arxiv.org/pdf/2507.04822)] [[code](https://github.com/MIV-XJTU/SeqGrowGraph?tab=readme-ov-file)] 9 | ## 2024 10 | 1. **Streammapnet**: Streaming mapping network for vectorized online hd map construction. WACV, 2024. [[paper](https://arxiv.org/pdf/2308.12570)] [[code](https://github.com/yuantianyuan01/StreamMapNet)] 11 | 2. **HybriMap**: Hybrid Clues Utilization for Effective Vectorized HD Map Construction. arXiv preprint arXiv:2404.11155 (2024). [[paper](https://arxiv.org/pdf/2404.11155)] 12 | 3. (**SatforHDMap**)Complementing Onboard Sensors with Satellite Maps: A New Perspective for HD Map Construction. ICRA, 2024. [[paper](https://arxiv.org/pdf/2308.15427)] [[code](https://github.com/xjtu-cs-gao/SatforHDMap)] 13 | 4. (**GeMap**)Online Vectorized HD Map Construction Using Geometry. ECCV, 2024. [[paper](https://arxiv.org/pdf/2312.03341)] [[code](https://github.com/cnzzx/GeMap)][[project page](https://invictus717.github.io/GeMap/)] 14 | 5. **HIMap**: HybrId Representation Learning for End-to-end Vectorized HD Map Construction. CVPR, 2024. [[paper](https://arxiv.org/pdf/2403.08639)] [[code](https://github.com/BritaryZhou/HIMap)] 15 | 6. **MGMap**: Mask-Guided Learning for Online Vectorized HD Map Construction. CVPR, 2024. [[paper](https://arxiv.org/pdf/2404.00876)] [[code](https://github.com/xiaolul2/MGMap)] 16 | 7. (**MapQR**)Leveraging Enhanced Queries of Point Sets for Vectorized Map Construction. ECCV, 2024. [[paper](https://arxiv.org/pdf/2402.17430)] [[code](https://github.com/HXMap/MapQR)] 17 | 8. **ADMap**: Anti-disturbance framework for vectorized HD map construction. ECCV, 2024. [[paper](https://arxiv.org/pdf/2401.13172)] [[code](https://github.com/hht1996ok/ADMap)] 18 | 9. **MapTracker**: Tracking with Strided Memory Fusion for Consistent Vector HD Mapping. ECCV, 2024. [[paper](https://arxiv.org/pdf/2403.15951)] [[code](https://github.com/woodfrog/maptracker)] [[project page](https://map-tracker.github.io/)] 19 | 10. (**SQD-MapNet**)Stream Query Denoising for Vectorized HD Map Construction. arXiv preprint arXiv:2401.09112 (2024). [[paper](https://arxiv.org/pdf/2401.09112)] 20 | 11. **P-MapNet**: Far-seeing Map ConstructorEnhanced by both SDMap and HDMap Priors. arXiv preprint arXiv:2403.10521 (2024). [[paper](https://arxiv.org/pdf/2403.10521)] [[code](https://github.com/jike5/P-MapNet)] [[project page](https://jike5.github.io/P-MapNet/)] 21 | 12. **BLOS-BEV**: Navigation Map Enhanced Lane Segmentation Network, Beyond Line of Sight. IEEE IV, 2024. [[paper](https://arxiv.org/abs/2407.08526)] 22 | 14. **PriorMapNet**: Enhancing Online Vectorized HD Map Construction with Priors. arXiv preprint arXiv:2408.08802 (2024). [[paper](https://www.arxiv.org/pdf/2408.08802)] 23 | 15. Enhancing Online Road Network Perception and Reasoning with Standard Definition Maps. IROS, 2024. [[paper](https://www.arxiv.org/pdf/2408.01471)] [[project page](https://henryzhangzhy.github.io/sdhdmap/)] 24 | 16. **LaneGraph2Seq**: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement. AAAI, 2024. [[paper](https://arxiv.org/pdf/2401.17609)] [[code](https://github.com/fudan-zvg/RoadNet)] 25 | 17. **TopoLogic**: An Interpretable Pipeline for Lane Topology Reasoning on Driving Scenes. arXiv preprint arXiv:2405.14747 (2024). [[paper](https://arxiv.org/pdf/2405.14747)] [[code](https://github.com/Franpin/TopoLogic)] 26 | 18. (**CGNet**)Continuity Preserving Online CenterLine Graph Learning. ECCV, 2024. [[paper](https://arxiv.org/pdf/2407.11337)] [[code](https://github.com/XiaoMi/CGNet)] 27 | 20. Online Temporal Fusion for Vectorized Map Construction in Mapless Autonomous Driving. arXiv preprint arXiv:2409.00593 (2024). [[paper](https://arxiv.org/pdf/2409.00593)] 28 | 21. **LGmap**: Local-to-Global Mapping Network for Online Long-Range Vectorized HD Map Construction. 2024 CVPR autonomous grand challenge mapless driving. arXiv:2406.13988 (2024). [[paper](https://arxiv.org/pdf/2406.13988)] 29 | 22. Leveraging SD Map to Assist the OpenLane Topology. 2024 CVPR autonomous grand challenge mapless driving. [[paper](https://opendrivelab.github.io/Challenge%202024/mapless_XIAOMIEV.pdf)] 30 | 23. **UniHDMap**: Unified Lane Elements Detection for Topology HD Map Construction. 2024 CVPR autonomous grand challenge mapless driving. [[paper](https://opendrivelab.github.io/Challenge%202024/mapless_CrazyFriday.pdf)] 31 | 24. **MapVision**: CVPR 2024 Autonomous Grand Challenge Mapless Driving Tech Report. 2024 CVPR autonomous grand challenge mapless driving. [[paper](https://opendrivelab.github.io/Challenge%202024/mapless_mapvision.pdf)] 32 | 25. Scene Perception and Reasoning with SD Map in Aligned Feature Space for Mapless Driving. 2024 CVPR autonomous grand challenge mapless driving. [[paper](https://opendrivelab.github.io/Challenge%202024/mapless_BoschXCASW.pdf)] 33 | 26. (**Topo2d**)Enhancing 3D Lane Detection and Topology Reasoning with 2D Lane Priors. arXiv preprint arXiv:2406.03105 (2024). [[paper](https://arxiv.org/pdf/2406.03105)] [[code](https://github.com/homothetic/Topo2D)] 34 | 27. (**HRMapNet**)Enhancing Vectorized Map Perception with Historical Rasterized Maps. ECCV, 2024. [[paper](https://arxiv.org/pdf/2409.00620)] [[code](https://github.com/HXMap/HRMapNet)] 35 | 28. Driving with Prior Maps: Unified Vector Prior Encoding for Autonomous Vehicle Mapping. arXiv preprint arXiv:2409.05352 (2024). [[paper](https://arxiv.org/pdf/2409.05352v2)] 36 | 29. **GenMapping**: Unleashing the Potential of Inverse Perspective Mapping for Robust Online HD Map Construction. arXiv preprint arXiv:2409.08688 (2024). [[paper](https://arxiv.org/pdf/2409.08688)] [[code](https://github.com/lynn-yu/GenMapping)] 37 | 30. **ExelMap**: Explainable Element-based HD-Map Change Detection and Update. arXiv preprint arXiv:2409.10178 (2024). [[paper](https://www.arxiv.org/pdf/2409.10178)] 38 | 31. **GlobalMapNet**: An Online Framework for Vectorized Global HD Map Construction. arXiv preprint arXiv:2409.10063 (2024). [[paper](https://www.arxiv.org/pdf/2409.10063)] 39 | 32. **DTCLMapper**: Dual Temporal Consistent Learning for Vectorized HD Map Construction. T-ITS, 2024. [[paper](https://arxiv.org/pdf/2405.05518)] 40 | 33. Exploring Real World Map Change Generalization of Prior-Informed HD Map Prediction Models. CVPR 2024, Workshop on Autonomous Driving. [[paper](https://arxiv.org/pdf/2406.01961)] 41 | 34. (**MapEX**)Mind the map! Accounting for existing map information when estimating online HDMaps from sensor data. arXiv preprint arXiv:2311.10517 (2024). [[paper](https://arxiv.org/pdf/2311.10517)] 42 | 35. (**MapDR**)Driving by the Rules: A Benchmark for Integrating Traffic Sign Regulations into Vectorized HD Map. arXiv preprint arXiv:2410.23780 (2024). [[paper](https://arxiv.org/pdf/2410.23780)] 43 | 36. Enhancing Lane Segment Perception and Topology Reasoning with Crowdsourcing Trajectory Priors. arXiv preprint arXiv:2411.17161 (2024). [[paper](https://arxiv.org/pdf/2411.17161)] 44 | 37. **MGMapNet**: Multi-Granularity Representation Learning for End-to-End Vectorized HD Map Construction. arXiv preprint arXiv:2410.07733 (2024). [[paper](https://arxiv.org/pdf/2410.07733)] 45 | 38. **OpenSatMap**: A Fine-grained High-resolution Satellite Dataset for Large-scale Map Construction.NeurIPS 2024. [[paper](https://arxiv.org/pdf/2410.23278)] [[code](https://github.com/OpenSatMap/OpenSatMap-offical)] [[project page](https://opensatmap.github.io)] 46 | ## 2023 47 | 1. (**BeMapNet**)End-to-end vectorized hd-map construction with piecewise bezier curve. CVPR, 2023. [[paper](https://arxiv.org/abs/2306.09700)] [[code](https://github.com/er-muyue/BeMapNet)] 48 | 2. **Maptrv2**: An end-to-end framework for online vectorized hd map construction. arXiv preprint arXiv:2308.05736 (2023). [[paper](https://arxiv.org/pdf/2308.05736)] [[code](https://github.com/hustvl/MapTR/tree/maptrv2?tab=readme-ov-file)] 49 | 3. **Pivotnet**: Vectorized pivot learning for end-to-end hd map construction. ICCV, 2023. [[paper](https://arxiv.org/pdf/2308.16477)] [[code](https://github.com/wenjie710/PivotNet)] 50 | 4. **Neural map prior for autonomous driving.** CVPR, 2023. [[paper](https://arxiv.org/pdf/2304.08481)] [[code](https://github.com/Tsinghua-MARS-Lab/neural_map_prior)] [[project page](https://tsinghua-mars-lab.github.io/neural_map_prior/)] 51 | 5. **Instagram**: Instance-level graph modeling for vectorized hd map learning. arXiv preprint arXiv:2301.04470 (2023). [[paper](https://arxiv.org/pdf/2301.04470)] 52 | 6. **Scalablemap**: Scalable map learning for online long-range vectorized hd map construction. arXiv preprint arXiv:2310.13378 (2023). [[paper](https://arxiv.org/pdf/2310.13378)][[code](https://github.com/jingy1yu/ScalableMap)] 53 | 7. **Machmap**: End-to-end vectorized solution for compact hd-map construction. arXiv preprint arXiv:2306.10301 (2023). [[paper](https://arxiv.org/pdf/2306.10301)] 54 | 8. (**MapVR**)Online Map Vectorization for Autonomous Driving: A Rasterization Perspective. NeurIPS, 2023. [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/file/654f61ecd998c9095d30d42c03b832aa-Paper-Conference.pdf)][[code](https://github.com/ZhangGongjie/MapVR)] 55 | 9. (**TopoNet**)Graph-based Topology Reasoning for Driving Scenes. arXiv preprint arXiv:2304.05277 (2023). [[paper](https://arxiv.org/pdf/2304.05277)][[code](https://github.com/OpenDriveLab/TopoNet)] 56 | 10. (**LaneGAP**)Lane Graph as Path: Continuity-preserving Path-wise Modeling for Online Lane Graph Construction. ECCV, 2024. [[paper](https://arxiv.org/pdf/2303.08815)][[code](https://github.com/hustvl/LaneGAP)] 57 | 11. (**SMERF**)Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps. arXiv preprint arXiv:2311.04079 (2023). [[paper](https://arxiv.org/pdf/2311.04079v1)] [code](https://github.com/NVlabs/SMERF)] 58 | 12. **Bi-Mapper**: Holistic BEV Semantic Mapping for Autonomous Driving. RA-L, 2023. [[paper](https://arxiv.org/pdf/2305.04205)][[code](https://github.com/lynn-yu/Bi-Mapper)] 59 | 13. **LaneSegNet**: Map Learning with Lane Segment Perception for Autonomous Driving. ICLR, 2024. [[paper](https://arxiv.org/pdf/2312.16108)][[code](https://github.com/OpenDriveLab/LaneSegNet)] 60 | 14. **MV-Map**: Offboard HD-Map Generation with Multi-view Consistency. ICCV, 2023. [[paper](https://arxiv.org/pdf/2305.08851)] [[code](https://github.com/ZiYang-xie/MV-Map)] 61 | 15. **NeMO**: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark. arXiv preprint arXiv:2306.04540 (2023). [[paper](https://arxiv.org/pdf/2306.04540)] 62 | 16. **InsMapper**: Exploring Inner-instance Information for Vectorized HD Mapping. arXiv preprint arXiv:2308.08543 (2023). [[paper](https://arxiv.org/pdf/2308.08543)] [[code](https://github.com/TonyXuQAQ/InsMapper)] [[project page](https://tonyxuqaq.github.io/InsMapper/)] 63 | 17. (**RoadNet**)Translating Images to Road Network: A Non-Autoregressive Sequence-to-Sequence Approach. ICCV, 2023(Oral). [[paper](https://arxiv.org/pdf/2402.08207)] [[code](https://github.com/fudan-zvg/RoadNet)] 64 | 18. **TopoMLP**: A Simple yet Strong Pipeline for Driving Topology Reasoning. ICLR, 2024. [[paper](https://arxiv.org/pdf/2310.06753)] [[code](https://github.com/wudongming97/TopoMLP)] 65 | 19. **TopoMask**: Instance-Mask-Based Formulation for the Road Topology Problem via Transformer-Based Architecture. arXiv preprint arXiv:2306.05419 (2023). [[paper](https://arxiv.org/pdf/2306.05419)] 66 | ## 2022 67 | 1. **Hdmapnet**: An online hd map construction and evaluation framework. ICRA, 2022. [[paper](https://arxiv.org/pdf/2107.06307)] [[code](https://github.com/Tsinghua-MARS-Lab/HDMapNet)] [[project page](https://tsinghua-mars-lab.github.io/HDMapNet/)] 68 | 2. **Vectormapnet**: End-to-end vectorized hd map learning. ICML, 2023. [[paper](https://arxiv.org/pdf/2206.08920)] [[code](https://github.com/Mrmoore98/VectorMapNet_code)][[project page](https://tsinghua-mars-lab.github.io/vectormapnet/)] 69 | 3. **CenterLineDet**: CenterLine Graph Detection for Road Lanes with Vehicle-mounted Sensors by Transformer for HD Map Generation. ICRA, 2023. [[paper](https://arxiv.org/pdf/2209.07734)] [[code](https://github.com/TonyXuQAQ/CenterLineDet)] [[project page](https://tonyxuqaq.github.io/projects/CenterLineDet/)] 70 | 4. **Maptr**: Structured modeling and learning for online vectorized hd map construction. ICLR, 2023. [[paper](https://arxiv.org/abs/2208.14437)] [[code](https://github.com/hustvl/MapTR?tab=readme-ov-file)] 71 | 72 | ## 2021 73 | 1. (**STSU**)Structured bird's-eye-view traffic scene understanding from onboard images. ICCV, 2021.[[paper](https://arxiv.org/pdf/2110.01997)][[code](https://github.com/ybarancan/STSU)][[project page](https://patrick-llgc.github.io/Learning-Deep-Learning/paper_notes/stsu.html)] 74 | 2. (**TPLR**)Topology Preserving Local Road Network Estimation from Single Onboard Camera Image. CVPR, 2022. [[paper](https://arxiv.org/pdf/2112.10155)] [[code](https://github.com/ybarancan/TopologicalLaneGraph)] 75 | --------------------------------------------------------------------------------