SJY-1995/GeoTikz-Base

---
dataset_id: GeoTikz-Base
license: cc-by-nc-4.0
language:
- en
tags:
- image-to-tikz
- geometry
- mathematical-diagrams
- tikz
- plane-geometry
- analytic-geometry
- geo-tikz
pretty_name: GeoTikz-Base
size_category: large
task_categories:
- image-to-text
---

# GeoTikzBridge: Advancing Multimodal Code Generation for Geometric Perception and Reasoning [CVPR2026]

## Table of Contents
1. [Dataset Summary](#dataset-summary)
2. [Dataset Structure](#dataset-structure)
3. [Dataset Creation](#dataset-creation)
4. [Dataset Distribution](#dataset-distribution)
5. [Citation](#citation)

---

## Dataset Summary
**GeoTikz-Base** is a 2.45M **image-to-TikZ dataset**. This dataset provides paired data consisting of original images and their corresponding TikZ code, serving as a foundational resource for research on geometric perception, mathematical reasoning, TikZ code synthesis, etc.

## Dataset Structure
Each sample in GeoTikz-Base is composed of:
1. `image`: image bytes
2. `question`: query to generate tikz code
3. `response`: generated tikz code

## Dataset Creation
The dataset is built using two core innovative strategies:
1. **Iterative Self-Refinement**
2. **Localized Transformation Strategy**
Please refer to our paper for details.

## Dataset Distribution
The distribution of GeoTikz-Base centers on **Plane Geometry** and **Analytic Geometry** as the primary components, also incorporating supplementary domains including Algebra, Calculus, and other mathematical fields, achieving full coverage of mainstream mathematical figures.
<img src="dataset-distribution.jpg" width="60%" alt="GeoTikz-Base Dataset Domain Distribution">

## Citation
Please cite the paper if you use our data, model or code:
```bibtex
@inproceedings{
geotikzbridge,
title={GeoTikzBridge: Advancing Multimodal Code Generation for Geometric Perception and Reasoning},
author={Jiayin Sun and Caixia Sun and Boyu Yang and Hailin Li and Xiao Chen and Yi Zhang and Errui Ding and Liang Li and Chao Deng and Junlan Feng},
booktitle={2026 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year={2026}
}