metadata
dataset_info:
features:
- name: idx
dtype: string
- name: Question
dtype: string
- name: Image
dtype: image
- name: Groundtruth
dtype: string
- name: Task
dtype: string
splits:
- name: full
num_bytes: 171585064
num_examples: 490
- name: HiddenText
num_bytes: 107144174
num_examples: 150
- name: 3DCaptcha
num_bytes: 399420
num_examples: 150
- name: Colorblind
num_bytes: 11984769
num_examples: 150
- name: ChineseLigature
num_bytes: 52056701
num_examples: 40
download_size: 343068512
dataset_size: 343170128
configs:
- config_name: default
data_files:
- split: full
path: data/full-*
- split: HiddenText
path: data/HiddenText-*
- split: 3DCaptcha
path: data/3DCaptcha-*
- split: Colorblind
path: data/Colorblind-*
- split: ChineseLigature
path: data/ChineseLigature-*
Data Description
The Turing Eye Test (TET) as presented in Paper 'Pixels, Patterns, But No Poetry: To See the World Like Humans'.
This benchmark includes four tasks:
- HiddenText: comprises scale-variant items where text is rendered as shapes within the figure, appearing as text when reduced and resolving into a complete image when magnified, which contains 150 images.
- 3DCaptcha: involves recognition challenges constructed with curved characters in the three-dimensional space, which consists of 150 Captchas.
- ColorBlind: similar to Ishihara tests, but augmented with confounding colored dots that are chromatically similar to the central character to increase difficulty. We generate 150 such test images.
- ChineseLigatures: features complex glyphs synthesized through character decomposition, morphological transformation, and fusion of multiple Chinese characters, which includes different words or phrases.
Citation
If you find this dataset is useful in your work, please cite our paper:
@misc{gao2025pixelspatternspoetryworld,
title={Pixels, Patterns, but No Poetry: To See The World like Humans},
author={Hongcheng Gao and Zihao Huang and Lin Xu and Jingyi Tang and Xinhao Li and Yue Liu and Haoyang Li and Taihang Hu and Minhua Lin and Xinlong Yang and Ge Wu and Balong Bi and Hongyu Chen and Wentao Zhang},
year={2025},
eprint={2507.16863},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2507.16863}
}