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 for 13 classes: misc, sky, building, road, sidewalk, fence, vegetation, pole, car, sign, pedestrian, cyclist, lane-marking.
Features:
- XLarge 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
- Automatic groundtruth: individual instances for semantic segmentation (pixelwise annotations), depth, car ego-motion