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

Repo for "Physion: Evaluating Physical Prediction from Vision in Humans and Machines" submission to NeurIPS 2021 (Datasets & Benchmarks track)

Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy

Cognitive Tools Lab 38 Jan 06, 2023
LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT

LightHuBERT LightHuBERT: Lightweight and Configurable Speech Representation Learning with Once-for-All Hidden-Unit BERT | Github | Huggingface | SUPER

WangRui 46 Dec 29, 2022
Semantic segmentation models, datasets and losses implemented in PyTorch.

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

Yassine 1.3k Jan 07, 2023
Here is the diagnostic tool for BMVC 2021 paper Diagnosing Errors in Video Relation Detectors.

Here is the diagnostic tool for BMVC 2021 paper Diagnosing Errors in Video Relation Detectors. We provide a tiny ground truth file demo_gt.json, and t

Shuo Chen 3 Dec 26, 2022
This is the latest version of the PULP SDK

PULP-SDK This is the latest version of the PULP SDK, which is under active development. The previous (now legacy) version, which is no longer supporte

78 Dec 07, 2022
Distributed Deep learning with Keras & Spark

Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc

Max Pumperla 1.6k Jan 05, 2023
BackgroundRemover lets you Remove Background from images and video with a simple command line interface

BackgroundRemover BackgroundRemover is a command line tool to remove background from video and image, made by nadermx to power https://BackgroundRemov

Johnathan Nader 1.7k Dec 30, 2022
Memory Efficient Attention (O(sqrt(n)) for Jax and PyTorch

Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo

Amin Rezaei 126 Dec 27, 2022
High level network definitions with pre-trained weights in TensorFlow

TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.

Taehoon Lee 1k Dec 13, 2022
Reimplementation of Dynamic Multi-scale filters for Semantic Segmentation.

Paddle implementation of Dynamic Multi-scale filters for Semantic Segmentation.

Hongqiang.Wang 2 Nov 01, 2021
Image process framework based on plugin like imagej, it is esay to glue with scipy.ndimage, scikit-image, opencv, simpleitk, mayavi...and any libraries based on numpy

Introduction ImagePy is an open source image processing framework written in Python. Its UI interface, image data structure and table data structure a

ImagePy 1.2k Dec 29, 2022
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"

Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie

Secure AI Systems Lab 8 Mar 26, 2022
Generic U-Net Tensorflow implementation for image segmentation

Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu

Joel Akeret 1.8k Dec 10, 2022
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"

PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"

Yulun Zhang 1.2k Dec 26, 2022
An Unsupervised Detection Framework for Chinese Jargons in the Darknet

An Unsupervised Detection Framework for Chinese Jargons in the Darknet This repo is the Python 3 implementation of 《An Unsupervised Detection Framewor

7 Nov 08, 2022
Genetic feature selection module for scikit-learn

sklearn-genetic Genetic feature selection module for scikit-learn Genetic algorithms mimic the process of natural selection to search for optimal valu

Manuel Calzolari 260 Dec 14, 2022
PyTorch implementation of UNet++ (Nested U-Net).

PyTorch implementation of UNet++ (Nested U-Net) This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architect

4ui_iurz1 642 Jan 04, 2023
PyTorch implementation for COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction (CVPR 2021)

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

XLearning Group 72 Dec 07, 2022
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration (NeurIPS 2021) PyTorch implementation of the paper: CoFiNet: Reli

76 Jan 03, 2023
SpanNER: Named EntityRe-/Recognition as Span Prediction

SpanNER: Named EntityRe-/Recognition as Span Prediction Overview | Demo | Installation | Preprocessing | Prepare Models | Running | System Combination

NeuLab 104 Dec 17, 2022