dangth2004/KITTI-Pseudo-Depth

KITTI Pseudo Depth (Eigen Split) with Depth Anything V2

Dataset Description

This dataset provides high-quality pseudo depth maps for the KITTI raw dataset, generated using the state-of-the-art Depth Anything V2 model. It is designed to facilitate research in Monocular Depth Estimation, 3D Object Detection, and autonomous driving applications.

The dataset follows the standard Eigen Split for training, validation, and testing.

• Original Image Source: KITTI Vision Benchmark Suite (Raw Data)
• Depth Generator: Depth Anything V2
• Data Format: RGB images in .png, Depth maps in .npy (float32) for zero-loss precision.

Citation & Acknowledgments

If you use this dataset in your research, please consider citing the original KITTI dataset and the authors of Depth Anything V2: Depth Anything V2:

@article{depth_anything_v2,
  title={Depth Anything V2},
  author={Yang, Lihe and Kang, Bingyi and Huang, Zilong and Zhao, Zhen and Xu, Xiaogang and Feng, Jiashi and Zhao, Hengshuang},
  journal={arXiv preprint arXiv:2406.09414},
  year={2024}
}

KITTI Dataset:

@article{Geiger2013IJRR,
  author = {Andreas Geiger and Philip Lenz and Christoph Stiller and Raquel Urtasun},
  title = {Vision meets Robotics: The KITTI Dataset},
  journal = {International Journal of Robotics Research (IJRR)},
  year = {2013}
}

@inproceedings{Menze2015CVPR,
  author = {Moritz Menze and Andreas Geiger},
  title = {Object Scene Flow for Autonomous Vehicles},
  booktitle = {Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2015}
}