HD semantic map learning
2 papers with code • 2 benchmarks • 2 datasets
The goal of task is to generate map elements in a vectorized form using data from onboard sensors, e.g., RGB cameras and/or LiDARs. These map elements include but are not limited to : Road boundaries, boundaries of roads that split roads and sidewalks.
Benchmarks
These leaderboards are used to track progress in HD semantic map learning
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nuScenes
TbV Dataset
Most implemented papers
HDMapNet: An Online HD Map Construction and Evaluation Framework
Tsinghua-MARS-Lab/HDMapNet
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By introducing the method and metrics, we invite the community to study this novel map learning problem.
VectorMapNet: End-to-end Vectorized HD Map Learning
Mrmoore98/VectorMapNet_code
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To the best of our knowledge, VectorMapNet is the first work designed towards end-to-end vectorized map learning from onboard observations.
