Code for database and frontend of webpage for Neural Fields in Visual Computing and Beyond.

Overview

Neural Fields in Visual Computing—Complementary Webpage

This is based on the amazing MiniConf project from Hendrik Strobelt and Sasha Rush—thank you!

Citation

If you find our project helpful, please cite our review paper:

@article{xie2021neuralfield,
    title = {Neural Fields in Visual Computing and Beyond},
    author = {Yiheng Xie and Towaki Takikawa and Shunsuke Saito and Or Litany and Shiqin Yan and Numair Khan
    and Federico Tombari and James Tompkin and Vincent Sitzmann and Srinath Sridhar},
    booktitle = {ArXiv Pre-print},
    year = {2021} 
}

Adding a paper—How To

See our website instructions

Website Team—Get Started on Development

> pip install -r requirements.txt
> make run

When you are ready to deploy run make freeze to get a static version of the site in the build folder.

Deploying to Github

  • Define two command-line variables GH_TOKEN and GH_REF. GH_TOKEN is your Github personal access token, and will look like username:token. GH_REF is the location of this repo, e.g., $> export GH_REF=github.com/brownvc/neural-fields-review.
  • DO NOT add GH_TOKEN to the Makefile—this is your personal access token and should be kept private. Hence, declare a temporary command line variable using export.
  • Commit any changes. Any uncommited changes will be OVERWRITTEN!
  • Execute make deploy.
  • That's it. The page is now live here.

Tour

The repo contains:

  1. Datastore sitedata/

Collection of CSV files representing the papers, speakers, workshops, and other important information for the conference.

  1. Routing main.py

One file flask-server handles simple data preprocessing and site navigation.

  1. Templates templates/

Contains all the pages for the site. See base.html for the master page and components.html for core components.

  1. Frontend static/

Contains frontend components like the default css, images, and javascript libs.

  1. Scripts scripts/

Contains additional preprocessing to add visualizations, recommendations, schedules to the conference.

  1. For importing calendars as schedule see scripts/README_Schedule.md

Extensions

MiniConf is designed to be a completely static solution. However it is designed to integrate well with dynamic third-party solutions. We directly support the following providers:

  • Rocket.Chat: The chat/ directory contains descriptions for setting up a hosted Rocket.Chat instance and for embedding chat rooms on individual paper pages. You can either buy a hosted setting from Rocket.chat or we include instructions for running your own scalable instance through sloppy.io.

  • Auth0 : The code can integrate through Auth0.com to provide both page login (through javascript gating) and OAuth SSO with Rocket Chat. The documentation on Auth0 is very easy to follow, you simply need to create an Application for both the MiniConf site and the Rocket.Chat server. You then enter in the Client keys to the appropriate configs.

  • SlidesLive: It is easy to embedded any video provider -> YouTube, Vimeo, etc. However we have had great experience with SlidesLive and recommend them as a host. We include a slideslive example on the main page.

  • PDF.js: For conferences that use posters it is easy to include an embedded pdf on poster pages. An example is given.

Owner
Brown University Visual Computing Group
Brown University Visual Computing Group
A Pose Estimator for Dense Reconstruction with the Structured Light Illumination Sensor

Phase-SLAM A Pose Estimator for Dense Reconstruction with the Structured Light Illumination Sensor This open source is written by MATLAB Run Mode Open

Xi Zheng 14 Dec 19, 2022
Toolbox to analyze temporal context invariance of deep neural networks

PyTCI A toolbox that estimates the integration window of a sensory response using the "Temporal Context Invariance" paradigm (TCI). The TCI method Int

4 Oct 23, 2022
Supplementary materials for ISMIR 2021 LBD paper "Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes"

Evaluation of Latent Space Disentanglement in the Presence of Interdependent Attributes Supplementary materials for ISMIR 2021 LBD submission: K. N. W

Karn Watcharasupat 2 Oct 25, 2021
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022

CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC

LEAP Lab 2 Sep 15, 2022
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.

Pyserini Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. Retrieval using sparse re

Castorini 706 Dec 29, 2022
Computer-Vision-Paper-Reviews - Computer Vision Paper Reviews with Key Summary along Papers & Codes

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

Jonathan Choi 2 Mar 17, 2022
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling

bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies

Achilles Rasquinha 1.8k Jan 05, 2023
Abstractive opinion summarization system (SelSum) and the largest dataset of Amazon product summaries (AmaSum). EMNLP 2021 conference paper.

Learning Opinion Summarizers by Selecting Informative Reviews This repository contains the codebase and the dataset for the corresponding EMNLP 2021

Arthur Bražinskas 39 Jan 01, 2023
DenseNet Implementation in Keras with ImageNet Pretrained Models

DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted

Felix Yu 568 Oct 31, 2022
QuanTaichi evaluation suite

QuanTaichi: A Compiler for Quantized Simulations (SIGGRAPH 2021) Yuanming Hu, Jiafeng Liu, Xuanda Yang, Mingkuan Xu, Ye Kuang, Weiwei Xu, Qiang Dai, W

Taichi Developers 120 Jan 04, 2023
This project hosts the code for implementing the ISAL algorithm for object detection and image classification

Influence Selection for Active Learning (ISAL) This project hosts the code for implementing the ISAL algorithm for object detection and image classifi

25 Sep 11, 2022
Chinese clinical named entity recognition using pre-trained BERT model

Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi

Xiangyang Li 109 Dec 14, 2022
Bootstrapped Unsupervised Sentence Representation Learning (ACL 2021)

Install first pip3 install -e . Training python3 training/unsupervised_tuning.py python3 training/supervised_tuning.py python3 training/multilingual_

yanzhang_nlp 26 Jul 22, 2022
Model-based reinforcement learning in TensorFlow

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

46 Nov 09, 2022
A Simplied Framework of GAN Inversion

Framework of GAN Inversion Introcuction You can implement your own inversion idea using our repo. We offer a full range of tuning settings (in hparams

Kangneng Zhou 13 Sep 27, 2022
M3DSSD: Monocular 3D Single Stage Object Detector

M3DSSD: Monocular 3D Single Stage Object Detector Setup pytorch 0.4.1 Preparation Download the full KITTI detection dataset. Then place a softlink (or

mumianyuxin 64 Dec 27, 2022
AdamW optimizer and cosine learning rate annealing with restarts

AdamW optimizer and cosine learning rate annealing with restarts This repository contains an implementation of AdamW optimization algorithm and cosine

Maksym Pyrozhok 133 Dec 20, 2022
Mini Software that give reminder to drink water as per your weight.

Water Notification Desktop Python The Mini Software built in Python (tkinter) that will remind you to drink water on specific time span based on your

Om Jogani 5 Dec 16, 2022
Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech

Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech This repository is the official implementation of "Meta-TTS: Meta-Learning for Few

Sung-Feng Huang 128 Dec 25, 2022
Real-time Joint Semantic Reasoning for Autonomous Driving

MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-

Marvin Teichmann 518 Dec 12, 2022