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Synthia Dataset

SYNTHetic collection of Imagery and Annotations for autonomous driving

Synthia Dataset

SYNTHIA, The SYNTHetic collection of Imagery and Annotations, is a dataset that has been generated with the purpose of aiding semantic segmentation and related scene understanding problems in the context of driving scenarios. SYNTHIA consists of a collection of photo-realistic frames rendered from a virtual city and comes with precise pixel-level semantic annotations.Features: Large volume of data & groundtruth: +200,000 HD images from video streams and +20,000 HD images from independent snapshots Scene diversity: European style town, modern city, highway and green areas Variety of dynamic objects: cars, pedestrians and cyclists Multiple seasons: dedicated themes for winter, fall, spring and summer Lighting conditions and weather: dynamic lights and shadows, several day-time modes, rain mode and night mode Sensor simulation: 8 RGB cameras forming a binocular 360º camera, 8 depth sensors

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Intel Labs & OSVF
https://www.intel.com/content/www/us/en/research/overview.html
Task
Autonomous Driving
Annotation Types
Semantic Segmentation
200000
Items
13
Classes
200000
Labels
Models using this dataset
Last updated on 
April 11, 2022
Licensed under 
Unknown
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