Researchers have introduced HRDX, a new large-scale dataset for constructing vector HD maps crucial for autonomous driving. Spanning approximately 1,400 km of driving data, HRDX is significantly larger than existing public datasets and includes richer semantic attributes and multimodal data like aerial imagery. The dataset aims to advance research in large-scale HD-map learning, multimodal BEV fusion, and the use of training-time privileged information, with experiments showing improvements in map construction quality. AI
IMPACT Enables more robust autonomous driving systems through improved HD map learning and multimodal fusion techniques.
RANK_REASON The cluster contains a research paper detailing a new dataset for autonomous driving map construction. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- BEV fusion
- DagsHub
- Gotit.pub
- HD Maps for Autonomous Vehicles: Implications for Cartographic Theory and Practice
- HRDX
- Hugging Face
- lidar
- RTK GNSS/IMU
- Sahith Reddy Chada
- ScienceCast
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