HRDX: A Large-Scale Vector HD-Map Dataset
Reliable autonomous driving requires vectorized HD maps that are geometrically accurate, semantically rich, and scalable to long-horizon driving. However, existing public HD map datasets are limited in scale, provide sparse semantic attributes, and lack modalities such as aerial imagery that could enable new research directions. We present HRDX, a large-scale dataset for vector HD-map construction, spanning about 40 hours (1,400 km) of minimally overlapping drives, which is several times larger than prior public HD map datasets. Data is captured using six synchronized surround cameras, a 128-beam LiDAR, and centimeter-level RTK GNSS/IMU, and is further complemented by precisely aligned ae...
| Authors | Sahith Reddy Chada, Isht Dwivedi, Nirav Savaliya |
|---|---|
| Primary category | cs.RO |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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