Datasets › SimBEV

SimBEV

Introduced by Goodarz Mehr et al. in SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset4 Feb 2025 archive 2025-07-28

The SimBEV dataset is a collection of 320 scenes spread across all 11 CARLA maps and contains data from a variety of sensors, including five camera types (RGB, semantic segmentation, instance segmentation, depth, and optical flow), lidar, semantic lidar, radar, GNSS, and IMU, along with 3D object bounding boxes and accurate bird's-eye view (BEV) ground truth. With each scene lasting 16 seconds at a frame rate of 20 Hz, the SimBEV dataset contains 102,400 annotated frames, over 8 million 3D object bounding boxes, and more than 2.5 billion BEV ground truth labels.

Benchmarks archive 2025-07-28

All 3 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

Papers archive 2025-07-28

1 shown of 1 paper with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 1. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset 1 15 4 Feb 2025 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

CC BY-NC-SA 4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • SimBEV

1 variant name, as the archive lists them.

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