Datasets › Songdo Vision

Songdo Vision (Songdo Vision: Vehicle Annotations from High-Altitude BeV Drone Imagery in a Smart City)

Introduced by Robert Fonod et al. in Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery17 Mar 2025 archive 2025-07-28

The Songdo Vision dataset provides high-resolution (4K, 3840×2160 pixels) RGB images annotated with categorized axis-aligned bounding boxes (BBs) for vehicle detection from a high-altitude bird’s-eye view (BeV) perspective. Captured over Songdo International Business District, South Korea, this dataset consists of 5,419 annotated video frames, featuring approximately 300,000 vehicle instances categorized into four classes:

  • Car (including vans and light-duty vehicles)
  • Bus
  • Truck
  • Motorcycle

Benchmarks archive 2025-07-28

All 1 leaderboard 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.

First row (archive order)PaperCode
Object Detection Songdo Vision Geo-trax Precision 0.911 Advanced computer vision for extracting georeferenced... rfonod/geo-trax 1 Compare

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
Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery 1 1 4 Nov 2024 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-4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • Songdo Vision

1 variant name, as the archive lists them.

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