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license: gpl-3.0 |
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pipeline_tag: depth-estimation |
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# LapDepth-release |
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/monocular-depth-estimation-using-laplacian/monocular-depth-estimation-on-kitti-eigen)](https://paperswithcode.com/sota/monocular-depth-estimation-on-kitti-eigen?p=monocular-depth-estimation-using-laplacian) |
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[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/monocular-depth-estimation-using-laplacian/monocular-depth-estimation-on-nyu-depth-v2)](https://paperswithcode.com/sota/monocular-depth-estimation-on-nyu-depth-v2?p=monocular-depth-estimation-using-laplacian) |
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This repository is a Pytorch implementation of the paper [**"Monocular Depth Estimation Using Laplacian Pyramid-Based Depth Residuals"**](https://ieeexplore.ieee.org/document/9316778) |
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![LapDepth](https://raw.githubusercontent.com/tjqansthd/LapDepth-release/master/example/FIG1.png) |
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Minsoo Song, Seokjae Lim, and [Wonjun Kim*](https://sites.google.com/view/dcvl) |
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IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) |
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# Official Repository: [LapDepth-release](https://github.com/tjqansthd/LapDepth-release) |
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# License: [GPL-3.0 license](https://github.com/tjqansthd/LapDepth-release/blob/master/LICENSE) |
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# Usage |
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```python |
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from model import LDRN |
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model = LDRN() |
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model.load_state_dict(torch.load("lap_depth_kitti.pkl"), strict=False) |
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model.eval() |
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``` |