https://github.com/amir22010/mono3d_plidar
Official PyTorch Implementation for "Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud"
Science Score: 10.0%
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Low similarity (5.4%) to scientific vocabulary
Last synced: 9 months ago
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Repository
Official PyTorch Implementation for "Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud"
Basic Info
- Host: GitHub
- Owner: Amir22010
- Default Branch: master
- Homepage: http://www.xinshuoweng.com/
- Size: 13.4 MB
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Fork of xinshuoweng/Mono3DPLiDAR
Created almost 7 years ago
· Last pushed almost 7 years ago
https://github.com/Amir22010/Mono3D_PLiDAR/blob/master/
# Monocular 3D Object Detection with Pseudo-LiDAR Point CloudThis repository contains the official PyTorch implementation for "[Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud](https://arxiv.org/pdf/1903.09847.pdf)". This paper has been accepted by IEEE International Conference on Computer Vision ([ICCV](http://iccv2019.thecvf.com/)) Workshops 2019. If you find the paper or the code useful, please cite our paper: ``` @article{Weng2019_Mono3D_PLiDAR, archivePrefix = {arXiv}, arxivId = {1903.09847}, author = {Weng, Xinshuo and Kitani, Kris}, eprint = {1903.09847}, journal = {arXiv:1903.09847}, title = {{Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud}}, url = {http://arxiv.org/abs/1903.09847.pdf}, year = {2019} } ``` # News 2019/06/29, we are applying for the license at CMU. The code will be released after we obtain the license.
Owner
- Name: Amir Khan
- Login: Amir22010
- Kind: user
- Location: India
- Repositories: 3
- Profile: https://github.com/Amir22010
working on developing a state of art AI solutions mainly in computer vision, chat bots and nlp domain. building an awesome AI as a professional developer 😍.
This repository contains the official PyTorch implementation for "[Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud](https://arxiv.org/pdf/1903.09847.pdf)". This paper has been accepted by IEEE International Conference on Computer Vision ([ICCV](http://iccv2019.thecvf.com/)) Workshops 2019. If you find the paper or the code useful, please cite our paper:
```
@article{Weng2019_Mono3D_PLiDAR,
archivePrefix = {arXiv},
arxivId = {1903.09847},
author = {Weng, Xinshuo and Kitani, Kris},
eprint = {1903.09847},
journal = {arXiv:1903.09847},
title = {{Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud}},
url = {http://arxiv.org/abs/1903.09847.pdf},
year = {2019}
}
```
# News
2019/06/29, we are applying for the license at CMU. The code will be released after we obtain the license.