Voxel-based Network for Shape Completion by Leveraging Edge Generation (ICCV 2021, oral)

Related tags

Deep LearningVE-PCN
Overview

Voxel-based Network for Shape Completion by Leveraging Edge Generation

This is the PyTorch implementation for the paper "Voxel-based Network for Shape Completion by Leveraging Edge Generation (ICCV 2021, oral)"

Getting Started

python version: python-3.6; cuda version: cuda-10; PyTorch version: 1.5

Compile Customized Operators

Build operators under ops by using python setup.py install.

Datasets

Our dataset PCN's dataset TopNet's dataset

Train the model

To train the models on pcn dataset: python train_edge.py
--train_pcn;
--loss_type: pcn;
--train_path: the training data;
--eval_path: the validation data;
--n_gt_points: 16384;
--n_out_points: 16384;
--density_weight:1e11;
--dense_cls_weight:1000;
--p_norm_weight:0;
--dist_regularize_weight:0;
--chamfer_weight:1e6;
--lr 0.0007.

To train the models on topnet dataset: python train_edge.py
--train_pcn;
--loss_type: topnet;
--train_path: the training data;
--eval_path: the validation data;
--n_gt_points: 2048;
--n_out_points: 2048;
--density_weight:1e10;
--dense_cls_weight:100;
--p_norm_weight:300;
--dist_regularize_weight:0.3;
--chamfer_weight:1e4;
--augment;
--lr 0.0007.

To train the models on our dataset: python train_edge.py
--train_seen;
--loss_type: topnet;
--h5_train: the training data;
--h5_val: the validation data;
--n_gt_points: 2048;
--n_out_points: 2048;
--density_weight:1e10;
--dense_cls_weight:100;
--p_norm_weight:300;
--dist_regularize_weight:0.3;
--chamfer_weight:1e4;
--lr 0.0007.

Evaluate the models

The pre-trained models can be downloaded here: Models, unzip and put them in the root directory.
To evaluate models: python test_edge.py
--loss_type: topnet or pcn;
--eval_path: the test data from different cases;
--checkpoint: the pre-trained models;
--num_gt_points: the resolution of ground truth point clouds.

Citation

@inproceedings{wang2021voxel,
     author = {Wang, Xiaogang and , Marcelo H. Ang Jr. and Lee, Gim Hee},
     title = {Voxel-based Network for Shape Completion by Leveraging Edge Generation},
     booktitle = {ICCV)},
     year = {2021},
}

Acknowledgements

Our implementations use the code from the following repository:
Chamferdistance
PointNet++
convolutional_point_cloud_decoder

Network Compression via Central Filter

Network Compression via Central Filter Environments The code has been tested in the following environments: Python 3.8 PyTorch 1.8.1 cuda 10.2 torchsu

2 May 12, 2022
Bolt Online Learning Toolbox

Bolt Online Learning Toolbox Bolt features discriminative learning of linear predictors (e.g. SVM or Logistic Regression) using fast online learning a

Peter Prettenhofer 87 Dec 12, 2022
PyTorch implementation of the REMIND method from our ECCV-2020 paper "REMIND Your Neural Network to Prevent Catastrophic Forgetting"

REMIND Your Neural Network to Prevent Catastrophic Forgetting This is a PyTorch implementation of the REMIND algorithm from our ECCV-2020 paper. An ar

Tyler Hayes 72 Nov 27, 2022
A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.

Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a

Justin 1.1k Dec 24, 2022
Object detection and instance segmentation toolkit based on PaddlePaddle.

Object detection and instance segmentation toolkit based on PaddlePaddle.

9.3k Jan 02, 2023
Data pipelines for both TensorFlow and PyTorch!

rapidnlp-datasets Data pipelines for both TensorFlow and PyTorch ! If you want to load public datasets, try: tensorflow/datasets huggingface/datasets

1 Dec 08, 2021
Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch

tonne 1.4k Dec 29, 2022
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning

Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu

Costas Mavromatis 21 Dec 03, 2022
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation Figure 1: We estimate the 6DoF rigid transformation of a 3D face (rendered in si

Vítor Albiero 519 Dec 29, 2022
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks

This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.

Richard Wang 443 Dec 06, 2022
This repo generates the training data and the model for Morpheus-Deblend

Morpheus-Deblend This repo generates the training data and the model for Morpheus-Deblend. This is the active development repo for the project and as

Ryan Hausen 2 Apr 18, 2022
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

Facebook Research 75 Dec 19, 2022
🥇 LG-AI-Challenge 2022 1위 솔루션 입니다.

LG-AI-Challenge-for-Plant-Classification Dacon에서 진행된 농업 환경 변화에 따른 작물 병해 진단 AI 경진대회 에 대한 코드입니다. (colab directory에 코드가 잘 정리 되어있습니다.) Requirements python

siwooyong 10 Jun 30, 2022
Publication describing 3 ML examples at NSLS-II and interfacing into Bluesky

Machine learning enabling high-throughput and remote operations at large-scale user facilities. Overview This repository contains the source code and

BNL 4 Sep 24, 2022
Controlling the MicriSpotAI robot from scratch

Project-MicroSpot-AI Controlling the MicriSpotAI robot from scratch Colaborators Alexander Dennis Components from MicroSpot The MicriSpotAI has the fo

Dennis Núñez-Fernández 5 Oct 20, 2022
Seq2seq - Sequence to Sequence Learning with Keras

Seq2seq Sequence to Sequence Learning with Keras Hi! You have just found Seq2Seq. Seq2Seq is a sequence to sequence learning add-on for the python dee

Fariz Rahman 3.1k Dec 18, 2022
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators

Pandas TA - A Technical Analysis Library in Python 3 Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package

Kevin Johnson 3.2k Jan 09, 2023
A DeepStack custom model for detecting common objects in dark/night images and videos.

DeepStack_ExDark This repository provides a custom DeepStack model that has been trained and can be used for creating a new object detection API for d

MOSES OLAFENWA 98 Dec 24, 2022
Dataset for the Research2Clinics @ NeurIPS 2021 Paper: What Do You See in this Patient? Behavioral Testing of Clinical NLP Models

Behavioral Testing of Clinical NLP Models This repository contains code for testing the behavior of clinical prediction models based on patient letter

Betty van Aken 2 Sep 20, 2022
A PyTorch Implementation of "Neural Arithmetic Logic Units"

Neural Arithmetic Logic Units [WIP] This is a PyTorch implementation of Neural Arithmetic Logic Units by Andrew Trask, Felix Hill, Scott Reed, Jack Ra

Kevin Zakka 181 Nov 18, 2022