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GEDepth: Ground Embedding for Monocular Depth Estimation (ICCV 2023)
GEDepth: Ground Embedding for Monocular Depth Estimation
Xiaodong Yang, Zhuang Ma, Zhiyu Ji, Zhe Ren
GEDepth: Ground Embedding for Monocular Depth Estimation, ICCV 2023
[Paper] [Poster]
Get Started
Installation
Please refer to INSTALL for the detail.
Data Preparation
Please follow the instructions in DATA.
Training and Evaluation
Please follow the instructions in RUN.
Main Results
DepthFormer is used in this repo as the baseline to exemplify the improvement by the proposed GEDepth. Please refer to the paper for more results, in particular, on the generalization enhancement.
- KITTI
| Model | Abs Rel | Sq Rel | RMSE | Checkpoint |
|---|---|---|---|---|
| Baseline | 0.052 | 0.156 | 2.133 | [Link] |
| GEDepth-Vanilla | 0.049 | 0.144 | 2.061 | [Google Drive] [Baidu Cloud] |
| GEDepth-Adaptive | 0.048 | 0.142 | 2.044 | [Google Drive] [Baidu Cloud] |
- DDAD
| Model | Abs Rel | Sq Rel | RMSE | Checkpoint |
|---|---|---|---|---|
| Baseline | 0.152 | 2.230 | 11.051 | [Link] |
| GEDepth-Vanilla | 0.147 | 2.155 | 10.784 | [Google Drive] [Baidu Cloud] |
| GEDepth-Adaptive | 0.145 | 2.146 | 10.672 | [Google Drive] [Baidu Cloud] |
Citation
Please cite the following paper if this repo helps your research:
@inproceedings{yang2023gedepth,
title={GEDepth: Ground Embedding for Monocular Depth Estimation},
author={Yang, Xiaodong and Ma, Zhuang and Ji, Zhiyu and Ren, Zhe},
booktitle={IEEE/CVF International Conference on Computer Vision (ICCV)},
year={2023}
}
License
Copyright (C) 2023 QCraft. All rights reserved. Licensed under the CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike 4.0 International). The code is released for academic research use only. For commercial use, please contact [email protected].
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