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
Pytorch implementation for reproducing StackGAN_v2 results in the paper StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks

StackGAN-v2 StackGAN-v1: Tensorflow implementation StackGAN-v1: Pytorch implementation Inception score evaluation Pytorch implementation for reproduci

Han Zhang 809 Dec 16, 2022
Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds."

DeltaConv [Paper] [Project page] Code for the SIGGRAPH 2022 paper "DeltaConv: Anisotropic Operators for Geometric Deep Learning on Point Clouds" by Ru

98 Nov 26, 2022
A universal framework for learning timestamp-level representations of time series

TS2Vec This repository contains the official implementation for the paper Learning Timestamp-Level Representations for Time Series with Hierarchical C

Zhihan Yue 284 Dec 30, 2022
A project to make Amazon Echo respond to sign language using your webcam

Making Alexa respond to Sign Language using Tensorflow.js Try the live demo Read the Blog Post on Tensorflow's Blog Coming Soon Watch the video This p

Abhishek Singh 444 Jan 03, 2023
RoMa: A lightweight library to deal with 3D rotations in PyTorch.

RoMa: A lightweight library to deal with 3D rotations in PyTorch. RoMa (which stands for Rotation Manipulation) provides differentiable mappings betwe

NAVER 90 Dec 27, 2022
Official PyTorch implementation of "Synthesis of Screentone Patterns of Manga Characters"

Manga Character Screentone Synthesis Official PyTorch implementation of "Synthesis of Screentone Patterns of Manga Characters" presented in IEEE ISM 2

Tsubota 2 Nov 20, 2021
Evaluating different engineering tricks that make RL work

Reinforcement Learning Tricks, Index This repository contains the code for the paper "Distilling Reinforcement Learning Tricks for Video Games". Short

Anssi 15 Dec 26, 2022
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)

ProbAI 2021 - Probabilistic Programming and Variational Inference Tutorial with Pryo Day 1 (June 14) Slides Notebook: students_PPLs_Intro Notebook: so

PGM-Lab 46 Nov 01, 2022
Json2Xml tool will help you convert from json COCO format to VOC xml format in Object Detection Problem.

JSON 2 XML All codes assume running from root directory. Please update the sys path at the beginning of the codes before running. Over View Json2Xml t

Nguyễn Trường Lâu 6 Aug 22, 2022
DNA sequence classification by Deep Neural Network

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

Mohammed Jawwadul Islam Fida 0 Aug 02, 2022
Python3 / PyTorch implementation of the following paper: Fine-grained Semantics-aware Representation Enhancement for Self-supervisedMonocular Depth Estimation. ICCV 2021 (oral)

FSRE-Depth This is a Python3 / PyTorch implementation of FSRE-Depth, as described in the following paper: Fine-grained Semantics-aware Representation

77 Dec 28, 2022
A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021)

GDN A tensorflow=1.13 implementation of Deconvolutional Networks on Graph Data (NeurIPS 2021) Abstract In this paper, we consider an inverse problem i

4 Sep 13, 2022
(AAAI2022) Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Semantic Segmentation

SM-PPM This is a Pytorch implementation of our paper "Style Mixing and Patchwise Prototypical Matching for One-Shot Unsupervised Domain Adaptive Seman

W-zx-Y 10 Dec 07, 2022
Code for pre-training CharacterBERT models (as well as BERT models).

Pre-training CharacterBERT (and BERT) This is a repository for pre-training BERT and CharacterBERT. DISCLAIMER: The code was largely adapted from an o

Hicham EL BOUKKOURI 31 Dec 05, 2022
This is the official repository of XVFI (eXtreme Video Frame Interpolation)

XVFI This is the official repository of XVFI (eXtreme Video Frame Interpolation), https://arxiv.org/abs/2103.16206 Last Update: 20210607 We provide th

Jihyong Oh 195 Dec 29, 2022
Kinetics-Data-Preprocessing

Kinetics-Data-Preprocessing Kinetics-400 and Kinetics-600 are common video recognition datasets used by popular video understanding projects like Slow

Kaihua Tang 7 Oct 27, 2022
DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021]

DiscoNet: Learning Distilled Collaboration Graph for Multi-Agent Perception [NeurIPS 2021] Yiming Li, Shunli Ren, Pengxiang Wu, Siheng Chen, Chen Feng

Automation and Intelligence for Civil Engineering (AI4CE) Lab @ NYU 98 Dec 21, 2022
PyTorch code for ICPR 2020 paper Future Urban Scene Generation Through Vehicle Synthesis

Future urban scene generation through vehicle synthesis This repository contains Pytorch code for the ICPR2020 paper "Future Urban Scene Generation Th

Alessandro Simoni 4 Oct 11, 2021
INSPIRED: A Transparent Dialogue Dataset for Interactive Semantic Parsing

INSPIRED: A Transparent Dialogue Dataset for Interactive Semantic Parsing Existing studies on semantic parsing focus primarily on mapping a natural-la

7 Aug 22, 2022
Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch

disclaimer: this code is modified from pytorch-tutorial Image classification with synthetic gradient in Pytorch I implement the Decoupled Neural Inter

Andrew 114 Dec 22, 2022