Mini-KITTI: a 48x48 dataset for tiny Monocular Depth Estimation
Dataset
This dataset scales down to 48x48 resolution the Eigen split of the KITTI dataset. It contains:
- A training split of 22600 images in 48x48 resolution
- A validation split of 888 images in 48x48 resolution
- A test split of 697 images in 48x48 resolution
All images are annotated with 48x48 depth and disparity maps obtained with the stereo-matching SGM algorithm. For every image, also a 360x360 centered portion of the original ground truth is provided, matching the same field of view of the respective image. If a 48x48 depth prediction related to a 48x48-sized image is upscaled to 360x360 resolution, these ground truth portions can be used to compute the prediction accuracy.
Usage
To use the dataset, simply:
tar -xzvf kitti_48x48.tar.gz -C ./
Then, you can find the dataset under "kitti_48x48/".
License
This dataset is derived from KITTI, and therefore released under CC-BY-NC-SA-3.0 license.
Citation
If you use this dataset, please cite:
@article{nadalini2025multi,
title={Multi-modal On-Device Learning for Monocular Depth Estimation on Ultra-low-power MCUs},
author={Nadalini, Davide and Rusci, Manuele and Cereda, Elia and Benini, Luca and Conti, Francesco and Palossi, Daniele},
journal={arXiv preprint arXiv:2512.00086},
year={2025}
}