Neural Factorization of Shape and Reflectance Under An Unknown Illumination

Overview

NeRFactor

[Paper] [Video] [Project]

teaser

This is the authors' code release for:

NeRFactor: Neural Factorization of Shape and Reflectance Under an Unknown Illumination
Xiuming Zhang, Pratul P. Srinivasan, Boyang Deng, Paul Debevec, William T. Freeman, Jonathan T. Barron
arXiv

This is not an officially supported Google product.

Setup

  1. Clone this repository:

    git clone https://github.com/google/nerfactor.git
  2. Install a Conda environment with all dependencies:

    cd nerfactor
    conda env create -f environment.yml
    conda activate nerfactor

Tips:

  • You can find the TensorFlow, cuDNN, and CUDA versions in environment.yml.
  • The IPython dependency in environment.yml is for IPython.embed() alone. If you are not using that to insert breakpoints during debugging, you can take it out (it should not hurt to just leave it there).

Data

If you are using our data, see the "Downloads" section of the project page.

If you are BYOD (bringing your own data), go to data_gen/ to either render your own synthetic data or process your real captures.

Running the Code

Go to nerfactor/ and follow the instructions there.

Issues or Questions?

If the issue is code-related, please open an issue here.

For questions, please also consider opening an issue as it may benefit future reader. Otherwise, email Xiuming Zhang.

Changelog

  • 06/01/2021: Initial release.
Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt)

Deep Learning for Natural Language Processing SS 2021 (TU Darmstadt) Task Training huge unsupervised deep neural networks yields to strong progress in

Oliver Hahn 1 Jan 26, 2022
This repository contains the data and code for the paper "Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors" ([email protected])

GP-VAE This repository provides datasets and code for preprocessing, training and testing models for the paper: Diverse Text Generation via Variationa

Wanyu Du 18 Dec 29, 2022
[NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators"

G-PATE This is the official code base for our NeurIPS 2021 paper: "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of T

AI Secure 14 Oct 12, 2022
Auto HMM: Automatic Discrete and Continous HMM including Model selection

Auto HMM: Automatic Discrete and Continous HMM including Model selection

Chess_champion 29 Dec 07, 2022
Accelerate Neural Net Training by Progressively Freezing Layers

FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra

Andy Brock 203 Jun 19, 2022
🌳 A Python-inspired implementation of the Optimum-Path Forest classifier.

OPFython: A Python-Inspired Optimum-Path Forest Classifier Welcome to OPFython. Note that this implementation relies purely on the standard LibOPF. Th

Gustavo Rosa 30 Jan 04, 2023
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

yobi byte 29 Oct 09, 2022
[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

Counterfactual VQA (CF-VQA) This repository is the Pytorch implementation of our paper "Counterfactual VQA: A Cause-Effect Look at Language Bias" in C

Yulei Niu 94 Dec 03, 2022
Net2net - Network-to-Network Translation with Conditional Invertible Neural Networks

Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri

CompVis Heidelberg 206 Dec 20, 2022
Implementation of the 😇 Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones

HaloNet - Pytorch Implementation of the Attention layer from the paper, Scaling Local Self-Attention For Parameter Efficient Visual Backbones. This re

Phil Wang 189 Nov 22, 2022
object detection; robust detection; ACM MM21 grand challenge; Security AI Challenger Phase VII

赛题背景 在商品知识产权领域,知识产权体现为在线商品的设计和品牌。不幸的是,在每一天,存在着非法商户通过一些对抗手段干扰商标识别来逃避侵权,这带来了很高的知识产权风险和财务损失。为了促进先进的多媒体人工智能技术的发展,以保护企业来之不易的创作和想法免受恶意使用和剽窃,因此提出了鲁棒性标识检测挑战赛

65 Dec 22, 2022
Perfect implement. Model shared. x0.5 (Top1:60.646) and 1.0x (Top1:69.402).

Shufflenet-v2-Pytorch Introduction This is a Pytorch implementation of faceplusplus's ShuffleNet-v2. For details, please read the following papers:

423 Dec 07, 2022
Official implementation for “Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior”

HEP Unsupervised Low-Light Image Enhancement via Histogram Equalization Prior Implementation Python3 PyTorch=1.0 NVIDIA GPU+CUDA Training process The

FengZhang 34 Dec 04, 2022
DeepMind Alchemy task environment: a meta-reinforcement learning benchmark

The DeepMind Alchemy environment is a meta-reinforcement learning benchmark that presents tasks sampled from a task distribution with deep underlying structure.

DeepMind 188 Dec 25, 2022
Gradient representations in ReLU networks as similarity functions

Gradient representations in ReLU networks as similarity functions by Dániel Rácz and Bálint Daróczy. This repo contains the python code related to our

1 Oct 08, 2021
GeneralOCR is open source Optical Character Recognition based on PyTorch.

Introduction GeneralOCR is open source Optical Character Recognition based on PyTorch. It makes a fidelity and useful tool to implement SOTA models on

57 Dec 29, 2022
Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR

UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-

Microsoft 282 Jan 09, 2023
The 1st place solution of track2 (Vehicle Re-Identification) in the NVIDIA AI City Challenge at CVPR 2021 Workshop.

AICITY2021_Track2_DMT The 1st place solution of track2 (Vehicle Re-Identification) in the NVIDIA AI City Challenge at CVPR 2021 Workshop. Introduction

Hao Luo 91 Dec 21, 2022
[ICCV'21] PlaneTR: Structure-Guided Transformers for 3D Plane Recovery

PlaneTR: Structure-Guided Transformers for 3D Plane Recovery This is the official implementation of our ICCV 2021 paper News There maybe some bugs in

73 Nov 30, 2022
A New Approach to Overgenerating and Scoring Abstractive Summaries

We provide the source code for the paper "A New Approach to Overgenerating and Scoring Abstractive Summaries" accepted at NAACL'21. If you find the code useful, please cite the following paper.

Kaiqiang Song 4 Apr 03, 2022