When using or referring to this SYNTHIA-SF in your research, please cite our BMVC 2017 paper [ pdf ], please check our terms of use.

Daniel Hernandez-Juarez, Lukas Schneider, Antonio Espinosa, David Vazquez, Antonio Lopez, Uwe Franke, Marc Pollefeys, Juan Carlos Moure; British Machine Vision Conference (BMVC), 2017

author = {Hernandez-Juarez, Daniel and Schneider, Lukas and Espinosa, Antonio and Vazquez, David and Lopez, Antonio M. and Franke, Uwe and Pollefeys, Marc and Moure, Juan Carlos},
title = {Slanted Stixels: Representing San Francisco’s Steepest Streets},
booktitle = {British Machine Vision Conference (BMVC), 2017},
year = {2017}




SYNTHIA-SF dataset (RGB, Depth and Semantic Segmentation GT)
Slanted Stixels: Representing San Francisco’s Steepest Streets (BMVC2017)
BMVC2017 Presentation



Video sequences subsets acquired at 5 FPS. There are 6 sequences featuring different scenarios and traffic conditions. There are 2224 images with associated ground truth used to check the accuracy of Slanted Stixels in our BMVC paper. For each sequence we provide useful information such as: left and right image, ground truth for semantic segmentation, instance segmentation, depth, and calibration parameters. The semantic classes are Cityscapes compatible, we consider: void, road, sidewalk, building, wall, fence, pole, traffic light, traffic sign, vegetation, terrain, sky, person, rider, car, truck, bus, train, motorcycle, bicycle, road lines, other, road works.

Download the SYNTHIA dataset

To download this file, please enter your name and email address below. We will send you an email with a link to your download.

Your Name*


Your Email*

Please, select only those items you want to download

Your email will only be used (rarely) to keep you informed about updates/bugfixes. We will not sell or hand your information to any third party. By downloading this file you accept our licensing conditions.