PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation

Overview

Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation

[Code] [Data] [Project Page]

Official PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation, published at ICCV 2021.

Have you ever looked at a painting and wondered what is the story behind it? This work presents a framework to bring art closer to people by generating comprehensive descriptions of fine-art paintings. Generating informative descriptions for artworks, however, is extremely challenging, as it requires to 1) describe multiple aspects of the image such as its style, content, or composition, and 2) provide background and contextual knowledge about the artist, their influences, or the historical period. To address these challenges, we introduce a multi-topic and knowledgeable art description framework, which modules the generated sentences according to three artistic topics and, additionally, enhances each description with external knowledge. The framework is validated through an exhaustive analysis, both quantitative and qualitative, as well as a comparative human evaluation, demonstrating outstanding results in terms of both topic diversity and information veracity.

Setup

Requirements

The code are tested under Python3.6 with the following packages:

torch==1.1.0
torchvision==0.2.2
numpy==1.16.2
visdom==0.1.8.9
transformers==2.1.1
nltk==3.2.3
stanfordcorenlp==3.9.1.1
scipy==1.3.1
pandas==0.25.1

Prepare Data

1.Download the dataset from this repository

2.Put the annotation folder into the MaskedSentenceGeneration

Masked Sentence Generation

cd MaskedSentenceGeneration
python prepare_dataset.py
bash train.sh
bash test_one.sh / bash test_all.sh

Knowledge Retrieval

Please look into here

Knowledge Filling

cd KnowledgeFilling
python create_dataset_drqa_src.py
bash train.sh
bash test.sh

Citation

If you find the data in this repository useful, please cite our paper:

@InProceedings{bai2021explain,
   author    = {Zechen Bai and Yuta Nakashima and Noa Garcia},
   title     = {Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation},
   booktitle = {International Conference in Computer Vision},
   year      = {2021},
}
Owner
Zechen Bai
No one designed us, we are just bad codes.
Zechen Bai
TextureGAN in Pytorch

TextureGAN This code is our PyTorch implementation of TextureGAN [Project] [Arxiv] TextureGAN is a generative adversarial network conditioned on sketc

Patsorn 147 Dec 14, 2022
HyperaPy: An automatic hyperparameter optimization framework ⚡🚀

hyperpy HyperPy: An automatic hyperparameter optimization framework Description HyperPy: Library for automatic hyperparameter optimization. Build on t

Sergio Mora 7 Sep 06, 2022
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo

chenxin 1 Dec 19, 2021
you can add any codes in any language by creating its respective folder (if already not available).

HACKTOBERFEST-2021-WEB-DEV Beginner-Hacktoberfest Need Your first pr for hacktoberfest 2k21 ? come on in About This is repository of Responsive Portfo

Suman Sharma 8 Oct 17, 2022
pyspark🍒🥭 is delicious,just eat it!😋😋

如何用10天吃掉pyspark? 🔥 🔥 《10天吃掉那只pyspark》 🚀

lyhue1991 578 Dec 30, 2022
Neural style transfer in PyTorch.

style-transfer-pytorch An implementation of neural style transfer (A Neural Algorithm of Artistic Style) in PyTorch, supporting CPUs and Nvidia GPUs.

Katherine Crowson 395 Jan 06, 2023
Text-to-Image generation

Generate vivid Images for Any (Chinese) text CogView is a pretrained (4B-param) transformer for text-to-image generation in general domain. Read our p

THUDM 1.3k Dec 29, 2022
Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning

radar-to-lidar-place-recognition This page is the coder of a pre-print, implemented by PyTorch. If you have some questions on this project, please fee

Huan Yin 37 Oct 09, 2022
Data augmentation for NLP, accepted at EMNLP 2021 Findings

AEDA: An Easier Data Augmentation Technique for Text Classification This is the code for the EMNLP 2021 paper AEDA: An Easier Data Augmentation Techni

Akbar Karimi 81 Dec 09, 2022
Official PyTorch implementation of GDWCT (CVPR 2019, oral)

This repository provides the official code of GDWCT, and it is written in PyTorch. Paper Image-to-Image Translation via Group-wise Deep Whitening-and-

WonwoongCho 135 Dec 02, 2022
LBBA-boosted WSOD

LBBA-boosted WSOD Summary Our code is based on ruotianluo/pytorch-faster-rcnn and WSCDN Sincerely thanks for your resources. Newer version of our code

Martin Dong 20 Sep 19, 2022
An open source Jetson Nano baseboard and tools to design your own.

My Jetson Nano Baseboard This basic baseboard gives the user the foundation and the flexibility to design their own baseboard for the Jetson Nano. It

NVIDIA AI IOT 57 Dec 29, 2022
Toontown House CT Edition

Toontown House: Classic Toontown House Classic source that should just work. ❓ W

Open Source Toontown Servers 5 Jan 09, 2022
official code for dynamic convolution decomposition

Revisiting Dynamic Convolution via Matrix Decomposition (ICLR 2021) A pytorch implementation of DCD. If you use this code in your research please cons

Yunsheng Li 110 Nov 23, 2022
Multi-tool reverse engineering collaboration solution.

CollaRE v0.3 Intorduction CollareRE is a tool for collaborative reverse engineering that aims to allow teams that do need to use more then one tool du

105 Nov 27, 2022
Official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch.

Multi-speaker DGP This repository provides official implementation of deep Gaussian process (DGP)-based multi-speaker speech synthesis with PyTorch. O

sarulab-speech 24 Sep 07, 2022
Indonesian Car License Plate Character Recognition using Tensorflow, Keras and OpenCV.

Monopol Indonesian Car License Plate (Indonesia Mobil Nomor Polisi) Character Recognition using Tensorflow, Keras and OpenCV. Background This applicat

Jayaku Briliantio 3 Apr 07, 2022
Einshape: DSL-based reshaping library for JAX and other frameworks.

Einshape: DSL-based reshaping library for JAX and other frameworks. The jnp.einsum op provides a DSL-based unified interface to matmul and tensordot o

DeepMind 62 Nov 30, 2022
PyTorch implementations of Generative Adversarial Networks.

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

Erik Linder-Norén 13.4k Jan 08, 2023
CUAD

Contract Understanding Atticus Dataset This repository contains code for the Contract Understanding Atticus Dataset (CUAD), a dataset for legal contra

The Atticus Project 273 Dec 17, 2022