A new benchmark for Icon Question Answering (IconQA) and a large-scale icon dataset Icon645.

Related tags

Deep LearningIconQA
Overview

IconQA

License: CC BY-SA 4.0

About

IconQA is a new diverse abstract visual question answering dataset that highlights the importance of abstract diagram understanding and comprehensive cognitive reasoning in real-world problems.

iconqa examples

There are three different sub-tasks in IconQA:

  • 57,672 image choice MC questions
  • 31,578 text chioce MC questions
  • 18,189 fill-in-the-blank questions
Sub-Tasks Train Validation Test Total
Multi-image-choice 34,603 11,535 11,535 57,672
Multi-text-choice 18,946 6,316 6,316 31,578
Filling-in-the-blank 10,913 3,638 3,638 18,189

In addition to IconQA, we also present Icon645, a large-scale dataset of icons that cover a wide range of objects:

  • 645,687 colored icons
  • 377 different icon classes

icon_examples

For more details, you can find our website here and our paper here.

Download

Our dataset is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Please read the license before you use, change, or share our dataset.

You can download IconQA here. Or run the commands by:

cd data
wget https://iconqa2021.s3.us-west-1.amazonaws.com/iconqa.zip
unzip iconqa.zip

You can download Icon645 here. Or run the commands by:

cd data
wget https://iconqa2021.s3.us-west-1.amazonaws.com/icon645.zip
unzip icon645.zip

File structures for the IconQA dataset:

IconQA
|   LICENSE.md
|   metadata.json
|   pid2skills.json
|   pid_splits.json
|   problems.json
|   skills.json
└───test
│   │
│   └───choose_img
│   |   |
│   |   └───question_id
│   |   |   |   image.png
|   |   |   |   data.json
|   |   |   |   choice_0.png
|   |   |   |   choice_1.png
|   |   |   |   ...
|   |   |
|   |   └───question_id
|   |   |   ...
|   |   
|   └───choose_txt
|   |   |  
|   |   └───question_id
|   |   |   |   image.png
|   |   |   |   data.json
|   |   | 
|   |   └───question_id
|   |   |   ...
|   |
|   └───fill_in_blank
|       |  
|       └───question_id
|       |   |   image.png
|       |   |   data.json
|       | 
|       └───question_id
|       |   ...
|   
└───train
|   |   same as test
|   
└───val
    |   same as test

File structures for the Icon645 dataset:

Icon645
|   LICENCE.md
|   metadata.json
└───colored_icons_final
    |
    └───acorn
    |   |   image_id1.png
    |   |   image_id2.png
    |   |   ...
    |   
    └───airplane
    |   |   image_id3.png
    |   |   ...
    |      
    |   ...

Citation

If the paper or the dataset inspires you, please cite us:

@inproceedings{lu2021iconqa,
  title = {IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning},
  author = {Lu, Pan and Qiu, Liang and Chen, Jiaqi and Xia, Tony and Zhao, Yizhou and Zhang, Wei and Yu, Zhou and Liang, Xiaodan and Zhu, Song-Chun},
  booktitle = {Submitted to the 35th Conference on Neural Information Processing Systems (NeurIPS 2021) Track on Datasets and Benchmarks},
  year = {2021}
}

License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

CC BY-NC-SA 4.0

Owner
Pan Lu
Computer Science
Pan Lu
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

DamoCV 25 Dec 16, 2022
TAPEX: Table Pre-training via Learning a Neural SQL Executor

TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE

Microsoft 157 Dec 28, 2022
ELSED: Enhanced Line SEgment Drawing

ELSED: Enhanced Line SEgment Drawing This repository contains the source code of ELSED: Enhanced Line SEgment Drawing the fastest line segment detecto

Iago Suárez 125 Dec 31, 2022
Implementation of Deformable Attention in Pytorch from the paper "Vision Transformer with Deformable Attention"

Deformable Attention Implementation of Deformable Attention from this paper in Pytorch, which appears to be an improvement to what was proposed in DET

Phil Wang 128 Dec 24, 2022
Reimplement of SimSwap training code

SimSwap-train Reimplement of SimSwap training code Instructions 1.Environment Preparation (1)Refer to the README document of SIMSWAP to configure the

seeprettyface.com 111 Dec 31, 2022
Final project for Intro to CS class.

Financial Analysis Web App https://share.streamlit.io/mayurk1/fin-web-app-final-project/webApp.py 1. Project Description This project is a technical a

Mayur Khanna 1 Dec 10, 2021
Count GitHub Stars ⭐

Count GitHub Stars per Day ⭐ Track GitHub stars per day over a date range to measure the open-source popularity of different repositories. Requirement

Ultralytics 20 Nov 20, 2022
Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018

UNet++: A Nested U-Net Architecture for Medical Image Segmentation UNet++ is a new general purpose image segmentation architecture for more accurate i

Zongwei Zhou 1.8k Jan 07, 2023
Saeed Lotfi 28 Dec 12, 2022
Code for "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds", CVPR 2021

PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou

Yi Wei 43 Dec 05, 2022
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding

Vision Longformer This project provides the source code for the vision longformer paper. Multi-Scale Vision Longformer: A New Vision Transformer for H

Microsoft 209 Dec 30, 2022
A PyTorch Implementation of Single Shot MultiBox Detector

SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragom

Max deGroot 4.8k Jan 07, 2023
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

mani 1.2k Jan 07, 2023
A comprehensive and up-to-date developer education platform for Urbit.

curriculum A comprehensive and up-to-date developer education platform for Urbit. This project organizes developer capabilities into a hierarchy of co

Sigilante 36 Oct 04, 2022
Multi-view 3D reconstruction using neural rendering. Unofficial implementation of UNISURF, VolSDF, NeuS and more.

Volume rendering + 3D implicit surface Showcase What? previous: surface rendering; now: volume rendering previous: NeRF's volume density; now: implici

Jianfei Guo 682 Jan 04, 2023
🦕 NanoSaur is a little tracked robot ROS2 enabled, made for an NVIDIA Jetson Nano

🦕 nanosaur NanoSaur is a little tracked robot ROS2 enabled, made for an NVIDIA Jetson Nano Website: nanosaur.ai Do you need an help? Discord For tech

NanoSaur 162 Dec 09, 2022
Contextualized Perturbation for Textual Adversarial Attack, NAACL 2021

Contextualized Perturbation for Textual Adversarial Attack Introduction This is a PyTorch implementation of Contextualized Perturbation for Textual Ad

cookielee77 30 Jan 01, 2023
[CVPR 2022 Oral] EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation

EPro-PnP EPro-PnP: Generalized End-to-End Probabilistic Perspective-n-Points for Monocular Object Pose Estimation In CVPR 2022 (Oral). [paper] Hanshen

同济大学智能汽车研究所综合感知研究组 ( Comprehensive Perception Research Group under Institute of Intelligent Vehicles, School of Automotive Studies, Tongji University) 842 Jan 04, 2023
This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector of the financial market.

GPlearn_finiance_stock_futures_extension This implementation contains the application of GPlearn's symbolic transformer on a commodity futures sector

Chengwei <a href=[email protected]"> 189 Dec 25, 2022
Video Matting via Consistency-Regularized Graph Neural Networks

Video Matting via Consistency-Regularized Graph Neural Networks Project Page | Real Data | Paper Installation Our code has been tested on Python 3.7,

41 Dec 26, 2022