Official Implementation (PyTorch) of "Point Cloud Augmentation with Weighted Local Transformations", ICCV 2021

Overview

PointWOLF: Point Cloud Augmentation with Weighted Local Transformations

This repository is the implementation of PointWOLF(To appear).

Sihyeon Kim1*, Sanghyeok Lee1*, Dasol Hwang1, Jaewon Lee1, Seong Jae Hwang2, Hyunwoo J. Kim1†, Point Cloud Augmentation with Weighted Local Transformations (ICCV 2021).
1Korea University 2University of Pittsburgh

PointWOLF_main

Installation

Dependencies

  • CUDA 10.2
  • Python 3.7.1
  • torch 1.7.0
  • packages : sklearn, numpy, h5py, glob

Download

Clone repository

$ git clone https://github.com/mlvlab/PointWOLF.git

Download ModelNet40

Notes : When you run the main.py, ModelNet40 is automatically downloaded at .../PointWOLF/data/.
If you want to download dataset on your ${PATH}, see below.

$ cd ${PATH}
$ wget https://shapenet.cs.stanford.edu/media/modelnet40_ply_hdf5_2048.zip --no-check-certificate
$ unzip modelnet40_ply_hdf5_2048.zip
$ rm modelnet40_ply_hdf5_2048.zip

Runnig the code

train

  • Run the training without PointWOLF & AugTune:
$ python main.py --exp_name=origin --model=dgcnn --num_points=1024 --k=20 --use_sgd=True
  • Run the training with PointWOLF:
$ python main.py --exp_name=PointWOLF --model=dgcnn --num_points=1024 --k=20 --use_sgd=True --PointWOLF
  • Run the training with PointWOLF & AugTune:
$ python main.py --exp_name=PointWOLF_AugTune --model=dgcnn --num_points=1024 --k=20 --use_sgd=True --PointWOLF --AugTune

eval

  • Run the evaluation with trained model located at ${PATH}:
$ python main.py --exp_name=eval --model=dgcnn --num_points=1024 --k=20 --use_sgd=True --eval=True --model_path=${PATH}

Citation

@InProceedings{Kim_2021_ICCV,
    author    = {Kim, Sihyeon and Lee, Sanghyeok and Hwang, Dasol and Lee, Jaewon and Hwang, Seong Jae and Kim, Hyunwoo J.},
    title     = {Point Cloud Augmentation With Weighted Local Transformations},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {548-557}
}

License

MIT License

Acknowledgement

The structure of this codebase is borrowed from DGCNN.

Owner
MLV Lab (Machine Learning and Vision Lab at Korea University)
MLV Lab (Machine Learning and Vision Lab at Korea University)
Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit

streamlit-manim Seeing if I can put together an interactive version of 3b1b's Manim in Streamlit Installation I had to install pango with sudo apt-get

Adrien Treuille 6 Aug 03, 2022
From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement (CVPR'2020)

Under-exposure introduces a series of visual degradation, i.e. decreased visibility, intensive noise, and biased color, etc. To address these problems, we propose a novel semi-supervised learning app

Yang Wenhan 117 Jan 03, 2023
Meta graph convolutional neural network-assisted resilient swarm communications

Resilient UAV Swarm Communications with Graph Convolutional Neural Network This repository contains the source codes of Resilient UAV Swarm Communicat

62 Dec 06, 2022
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space

Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte

38 Dec 15, 2022
Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators..

ARAPReg Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators.. Installation The cod

Bo Sun 132 Nov 28, 2022
This is the official source code of "BiCAT: Bi-Chronological Augmentation of Transformer for Sequential Recommendation".

BiCAT This is our TensorFlow implementation for the paper: "BiCAT: Sequential Recommendation with Bidirectional Chronological Augmentation of Transfor

John 15 Dec 06, 2022
Trading Strategies for Freqtrade

Freqtrade Strategies Strategies for Freqtrade, developed primarily in a partnership between @werkkrew and @JimmyNixx from the Freqtrade Discord. Use t

Bryan Chain 242 Jan 07, 2023
Pytorch Implementation of LNSNet for Superpixel Segmentation

LNSNet Overview Official implementation of Learning the Superpixel in a Non-iterative and Lifelong Manner (CVPR'21) Learning Strategy The proposed LNS

42 Oct 11, 2022
🍅🍅🍅YOLOv5-Lite: lighter, faster and easier to deploy. Evolved from yolov5 and the size of model is only 1.7M (int8) and 3.3M (fp16). It can reach 10+ FPS on the Raspberry Pi 4B when the input size is 320×320~

YOLOv5-Lite:lighter, faster and easier to deploy Perform a series of ablation experiments on yolov5 to make it lighter (smaller Flops, lower memory, a

pogg 1.5k Jan 05, 2023
This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their coordinates and detected labels.

This YoloV5 based model is fit to detect people and different types of land vehicles, and displaying their density on a fitted map, according to their

Liron Bdolah 8 May 22, 2022
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

5 Feb 04, 2022
Code release of paper Improving neural implicit surfaces geometry with patch warping

NeuralWarp: Improving neural implicit surfaces geometry with patch warping Project page | Paper Code release of paper Improving neural implicit surfac

François Darmon 167 Dec 30, 2022
An educational tool to introduce AI planning concepts using mobile manipulator robots.

JEDAI Explains Decision-Making AI Virtual Machine Image The recommended way of using JEDAI is to use pre-configured Virtual Machine image that is avai

Autonomous Agents and Intelligent Robots 13 Nov 15, 2022
a practicable framework used in Deep Learning. So far UDL only provide DCFNet implementation for the ICCV paper (Dynamic Cross Feature Fusion for Remote Sensing Pansharpening)

UDL UDL is a practicable framework used in Deep Learning (computer vision). Benchmark codes, results and models are available in UDL, please contact @

Xiao Wu 11 Sep 30, 2022
Kindle is an easy model build package for PyTorch.

Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? wh

Jongkuk Lim 77 Nov 11, 2022
AI virtual gym is an AI program which can be used to exercise and can be used to see if we are doing the exercises

AI virtual gym is an AI program which can be used to exercise and can be used to see if we are doing the exercises

4 Feb 13, 2022
neural image generation

pixray Pixray is an image generation system. It combines previous ideas including: Perception Engines which uses image augmentation and iteratively op

dribnet 398 Dec 17, 2022
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

Jungbeom Lee 81 Dec 16, 2022
Efficient Speech Processing Tookit for Automatic Speaker Recognition

Sugar Efficient Speech Processing Tookit for Automatic Speaker Recognition | HuggingFace | What's New EfficientTDNN: Efficient Architecture Search for

WangRui 14 Sep 14, 2022
Constraint-based geometry sketcher for blender

Constraint-based sketcher addon for Blender that allows to create precise 2d shapes by defining a set of geometric constraints like tangent, distance,

1.7k Dec 31, 2022