https://github.com/ardianumam/PointMixSwap
This is the official repository of our ECCV 2022 paper, "Point MixSwap: Attentional Point Cloud Mixing via Swapping Matched Structural Divisions".
https://github.com/ardianumam/PointMixSwap
Last synced: about 2 months ago
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This is the official repository of our ECCV 2022 paper, "Point MixSwap: Attentional Point Cloud Mixing via Swapping Matched Structural Divisions".
- Host: GitHub
- URL: https://github.com/ardianumam/PointMixSwap
- Owner: ardianumam
- Created: 2022-07-11T04:24:24.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2022-10-26T07:47:33.000Z (almost 3 years ago)
- Last Synced: 2024-12-16T02:34:35.678Z (10 months ago)
- Language: Python
- Homepage:
- Size: 35.1 MB
- Stars: 13
- Watchers: 2
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
# Point MixSwap
This is the official repository of our ECCV 2022 paper, "Point MixSwap: Attentional Point Cloud Mixing via Swapping Matched Structural Divisions".
### Dataset
Prepare ModelNet40 dataset by downloading it via [this link](https://shapenet.cs.stanford.edu/media/modelnet40_ply_hdf5_2048.zip). Then, extract the zip file and move to folder such that the structure becomes: `data/modelnet40_ply_hdf5_2048`.
### Train
To train the model, DGCNN with ModelNet40, run the script below (e.g., using the first GPU device):
```CUDA_VISIBLE_DEVICES=0 python main.py --config=configs/config.yaml```
Note: the code is tested in NVIDIA GeForce RTX 3090, using pyhton 3.9 with Ubuntu 18.04.5 LTS.
### Config
Yaml config file can be found in `configs` folder. The file contains all the hyperparamters setup and other related configurations. Most of them are self-explanatory by looking the variable names. Here some details:
* `MIXUP_LEVEL`: where to perform the mixup data, which can be `input`, `feature` and `both`
* `input`: perform mixup in the input model
* `feature`: perform mixup in the feature model
* `both`: perform mixup in both input and feature model
### Some Visualizations
### Cite
```
@article{pointmixswap,
author = {Umam, Ardian and Yang, Cheng-Kun and Chuang, Yung-Yu and Chuang, Jen-Hui and Lin, Yen-Yu},
title = {Point MixSwap: Attentional Point Cloud Mixing via Swapping Matched Structural Divisions},
booktitle={European Conference on Computer Vision},
year={2022}
}
```