[CVPR'21] DeepSurfels: Learning Online Appearance Fusion

Overview

DeepSurfels: Learning Online Appearance Fusion

Paper | Video | Project Page

pipeline

This is the official implementation of the CVPR 2021 submission DeepSurfels: Learning Online Appearance Fusion

DeepSurfels is a novel 3D representation for geometry and appearance information that combines planar surface primitives with voxel grid representation for improved scalability and rendering quality.

If you find our code or paper useful, please consider citing

@InProceedings{DeepSurfels:CVPR:21,
    title = {{DeepSurfels}: Learning Online Appearance Fusion},
    author = {Mihajlovic, Marko and Weder, Silvan and Pollefeys, Marc and Oswald, Martin R.},
    booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month = {June},
    year = {2021},
}

Contact Marko Mihajlovic for questions or open an issue / a pull request.

Installation

The prerequest is to install python packages specified in the requirements.txt file, which can conveniently accomplished by using an Anaconda environment.

# clone the repo
git clone https://github.com/onlinereconstruction/deep_surfels.git
cd ./deep_surfels

# create environment
conda env create -f environment.yml
conda activate deep_surfels

Then install the deep_surfel package via pip

pip install ./deep_surfel

Data

Directory ./data_prep/data_samples contains preprocessed toy data samples. See ./data_prep/from_depth_frames.py on how to prepare your own dataset.

Usage

To run the deterministic fusion:

cd appearance_fusion
python test.py -c ../configurations/sample_deterministic.yml --extract_meshes

To trained the learned module:

python train.py -c ../configurations/sample.yml

To evaluate the trained module:

python test.py -c ../configurations/sample.yml --extract_meshes

The rendered images will be stored in the specified logging_root_dir directory. See ./appearance_fusion/config.py for all available configuration parameters.

Lava-DL, but with PyTorch-Lightning flavour

Deep learning project seed Use this seed to start new deep learning / ML projects. Built in setup.py Built in requirements Examples with MNIST Badges

Sami BARCHID 4 Oct 31, 2022
PyTorch Implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedding (ORAL, MICCAIW 2021)

Small Lesion Segmentation in Brain MRIs with Subpixel Embedding PyTorch implementation of Small Lesion Segmentation in Brain MRIs with Subpixel Embedd

22 Oct 21, 2022
Diffusion Normalizing Flow (DiffFlow) Neurips2021

Diffusion Normalizing Flow (DiffFlow) Reproduce setup environment The repo heavily depends on jam, a personal toolbox developed by Qsh.zh. The API may

76 Jan 01, 2023
This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled Time Series presented at Causal Analysis Workshop 2021.

signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled

Will Glad 1 Mar 11, 2022
The source code for the Cutoff data augmentation approach proposed in this paper: "A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation".

Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in

Dinghan Shen 49 Dec 22, 2022
code for Fast Point Cloud Registration with Optimal Transport

robot This is the repository for the paper "Accurate Point Cloud Registration with Robust Optimal Transport". We are in the process of refactoring the

28 Jan 04, 2023
Experiments with Fourier layers on simulation data.

Factorized Fourier Neural Operators This repository contains the code to reproduce the results in our NeurIPS 2021 ML4PS workshop paper, Factorized Fo

Alasdair Tran 57 Dec 25, 2022
ARKitScenes - A Diverse Real-World Dataset for 3D Indoor Scene Understanding Using Mobile RGB-D Data

ARKitScenes This repo accompanies the research paper, ARKitScenes - A Diverse Real-World Dataset for 3D Indoor Scene Understanding Using Mobile RGB-D

Apple 371 Jan 05, 2023
Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.

Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.

Seulki Park 70 Jan 03, 2023
Domain Generalization with MixStyle, ICLR'21.

MixStyle This repo contains the code of our ICLR'21 paper, "Domain Generalization with MixStyle". The OpenReview link is https://openreview.net/forum?

Kaiyang 208 Dec 28, 2022
Boundary-preserving Mask R-CNN (ECCV 2020)

BMaskR-CNN This code is developed on Detectron2 Boundary-preserving Mask R-CNN ECCV 2020 Tianheng Cheng, Xinggang Wang, Lichao Huang, Wenyu Liu Video

Hust Visual Learning Team 178 Nov 28, 2022
A PyTorch-centric hybrid classical-quantum machine learning framework

torchquantum A PyTorch-centric hybrid classical-quantum dynamic neural networks framework. News Add a simple example script using quantum gates to do

MIT HAN Lab 400 Jan 02, 2023
This repository provides an efficient PyTorch-based library for training deep models.

s3sec Test AWS S3 buckets for read/write/delete access This tool was developed to quickly test a list of s3 buckets for public read, write and delete

Bytedance Inc. 123 Jan 05, 2023
Code for "Discovering Non-monotonic Autoregressive Orderings with Variational Inference" (paper and code updated from ICLR 2021)

Discovering Non-monotonic Autoregressive Orderings with Variational Inference Description This package contains the source code implementation of the

Xuanlin (Simon) Li 10 Dec 29, 2022
Convolutional neural network that analyzes self-generated images in a variety of languages to find etymological similarities

This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer

1 Feb 03, 2022
Official implement of "CAT: Cross Attention in Vision Transformer".

CAT: Cross Attention in Vision Transformer This is official implement of "CAT: Cross Attention in Vision Transformer". Abstract Since Transformer has

100 Dec 15, 2022
Multi-task head pose estimation in-the-wild

Multi-task head pose estimation in-the-wild We provide C++ code in order to replicate the head-pose experiments in our paper https://ieeexplore.ieee.o

Roberto Valle 26 Oct 06, 2022
Differential fuzzing for the masses!

NEZHA NEZHA is an efficient and domain-independent differential fuzzer developed at Columbia University. NEZHA exploits the behavioral asymmetries bet

147 Dec 05, 2022
A cool little repl-based simulation written in Python

A cool little repl-based simulation written in Python planned to integrate machine-learning into itself to have AI battle to the death before your eye

Em 6 Sep 17, 2022
[CVPR 2022] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels

Using Unreliable Pseudo Labels Official PyTorch implementation of Semi-Supervised Semantic Segmentation Using Unreliable Pseudo Labels, CVPR 2022. Ple

Haochen Wang 268 Dec 24, 2022