MOTSynth

A huge dataset for pedestrian detection and tracking in urban scenarios

Released in: MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?

Contributor:

by

Homepage

Summary

MOTSynth is a huge dataset for pedestrian detection and tracking in urban scenarios created by exploiting the highly photorealistic video game Grand Theft Auto V developed by Rockstar North. It contains a set of 764 full-HD videos, 1800 frames long, recorded at 20 fps. MOTSynth is born from the collaboration between UNIMORE and the Technical University of Munich.

1375200

Images in dataset

2021

Year Released

Key Links & Stats

@inproceedings{fabbri21iccv, title = {MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?}, author = {Matteo Fabbri and Guillem Bras{\'o} and Gianluca Maugeri and Aljo{\v{s}}a O{\v{s}}ep and Riccardo Gasparini and Orcun Cetintas and Simone Calderara and Laura Leal-Taix{\'e} and Rita Cucchiara}, booktitle = {International Conference on Computer Vision (ICCV)}, year = {2021} }

scenebox

Modalities

  1. Video

Verticals

  1. A/V
  2. Digital Human

ML Task

  1. Object Detection
  2. Semantic Segmentation
  3. Instance Segmentation
  4. Human Pose Estimation
  5. Object Tracking

Related organizations