Code for TIP 2017 paper --- Illumination Decomposition for Photograph with Multiple Light Sources.

Overview

Illumination_Decomposition

Code for TIP 2017 paper --- Illumination Decomposition for Photograph with Multiple Light Sources.

This code implements the core part of illumination decomposition in our paper via Visual Studio. Please add it to your project. The only dependency is OpenCV. We adopted an old OpenCV (1.X) naming style. You can rewrite it to adapt more recent ones.

If you use it for your research, please cite the following paper in your work:

Ling Zhang, Qingan Yan, Zheng Liu, Hua Zou, Chunxia Xiao. Illumination Decomposition for Photograph with Multiple Light Sources. IEEE Transactions on Image Processing (TIP), 2017.

@article{zhang2017illumination,
  title={Illumination Decomposition for Photograph With Multiple Light Sources},
  author={Zhang, Ling and Yan, Qingan and Liu, Zheng and Zou, Hua and Xiao, Chunxia},
  journal={IEEE Transactions on Image Processing},
  volume={26},
  number={9},
  pages={4114--4127},
  year={2017},
  publisher={IEEE}
}
Owner
QAY
Canon in D
QAY
COPA-SSE contains crowdsourced explanations for the Balanced COPA dataset

COPA-SSE Repository for COPA-SSE: Semi-Structured Explanations for Commonsense Reasoning. COPA-SSE contains crowdsourced explanations for the Balanced

Ana Brassard 5 Jul 31, 2022
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang

Young Kyun Jang 71 Dec 27, 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
An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available actions

Agar.io_Q-Learning_AI An experiment on the performance of homemade Q-learning AIs in Agar.io depending on their state representation and available act

1 Jun 09, 2022
The repository contain code for building compiler using puthon.

Building Compiler This is a python implementation of JamieBuild's "Super Tiny Compiler" Overview JamieBuilds developed a wonderfully educative compile

Shyam Das Shrestha 1 Nov 21, 2021
Running AlphaFold2 (from ColabFold) in Azure Machine Learning

Running AlphaFold2 (from ColabFold) in Azure Machine Learning Colby T. Ford, Ph.D. Companion repository for Medium Post: How to predict many protein s

Colby T. Ford 3 Feb 18, 2022
Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022)

Retinal Vessel Segmentation with Pixel-wise Adaptive Filters (ISBI 2022) Introdu

anonymous 14 Oct 27, 2022
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

4.8k Jan 07, 2023
rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle.

rastrainer rastrainer is a QGIS plugin to training remote sensing semantic segmentation model based on PaddlePaddle. UI TODO Init UI. Add Block. Add l

deepbands 5 Mar 04, 2022
Sharing of contents on mitochondrial encounter networks

mito-network-sharing Sharing of contents on mitochondrial encounter networks Required: R with igraph, brainGraph, ggplot2, and XML libraries; igraph l

Stochastic Biology Group 0 Oct 01, 2021
Tooling for converting STAC metadata to ODC data model

手语识别 0、使用到的模型 (1). openpose,作者:CMU-Perceptual-Computing-Lab https://github.com/CMU-Perceptual-Computing-Lab/openpose (2). 图像分类classification,作者:Bubbl

Open Data Cube 65 Dec 20, 2022
Bootstrapped Representation Learning on Graphs

Bootstrapped Representation Learning on Graphs This is the PyTorch implementation of BGRL Bootstrapped Representation Learning on Graphs The main scri

NerDS Lab :: Neural Data Science Lab 55 Jan 07, 2023
On Evaluation Metrics for Graph Generative Models

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

13 Jan 07, 2023
A Python Package for Convex Regression and Frontier Estimation

pyStoNED pyStoNED is a Python package that provides functions for estimating multivariate convex regression, convex quantile regression, convex expect

Sheng Dai 17 Jan 08, 2023
Improving Compound Activity Classification via Deep Transfer and Representation Learning

Improving Compound Activity Classification via Deep Transfer and Representation Learning This repository is the official implementation of Improving C

NingLab 2 Nov 24, 2021
Faune proche - Retrieval of Faune-France data near a google maps location

faune_proche Récupération des données de Faune-France près d'un lieu google maps

4 Feb 15, 2022
DFM: A Performance Baseline for Deep Feature Matching

DFM: A Performance Baseline for Deep Feature Matching Python (Pytorch) and Matlab (MatConvNet) implementations of our paper DFM: A Performance Baselin

143 Jan 02, 2023
Yolact-keras实例分割模型在keras当中的实现

Yolact-keras实例分割模型在keras当中的实现 目录 性能情况 Performance 所需环境 Environment 文件下载 Download 训练步骤 How2train 预测步骤 How2predict 评估步骤 How2eval 参考资料 Reference 性能情况 训练数

Bubbliiiing 11 Dec 26, 2022
Parallel Latent Tree-Induction for Faster Sequence Encoding

FastTrees This repository contains the experimental code supporting the FastTrees paper by Bill Pung. Software Requirements Python 3.6, NLTK and PyTor

Bill Pung 4 Mar 29, 2022
Official PyTorch implementation of UACANet: Uncertainty Aware Context Attention for Polyp Segmentation

UACANet: Uncertainty Aware Context Attention for Polyp Segmentation Official pytorch implementation of UACANet: Uncertainty Aware Context Attention fo

Taehun Kim 85 Dec 14, 2022