Datasets:

ShyFoo
/

CountHallu-Dataset-SimObject

license: apache-2.0
pretty_name: CountHalluSet — SimObject
task_categories:
  - unconditional-image-generation
  - image-classification
size_categories:
  - 10K<n<100K
tags:
  - diffusion
  - counting
  - hallucination
  - rendered

CountHalluSet — SimObject

Rendered dataset from Counting Hallucinations in Diffusion Models (arXiv:2510.13080). Part of CountHalluSet, a suite with well-defined counting criteria used to measure counting hallucination — a diffusion model generating the wrong number of instances, even for patterns absent from its training data.

What's inside

256×256 RGB rendered images of everyday objects, each labelled with the per-class instance count over three object classes. As with ToyShape, a correct sample contains at most one instance per class; extra or missing instances are counting hallucinations.

SimObject/
├── images/       # 00000.png, 00001.png, ...
└── labels.csv    # filename, <class_1>, <class_2>, <class_3>

Usage

huggingface-cli download ShyFoo/CountHallu-dataset-SimObject \
    --repo-type dataset --local-dir $DATASET_ROOT/SimObject

Load with the reference code (counthallu.datasets.SimObject). See the CountHallu repository for training and the full evaluation protocol.

Citation

@article{fu2025counting,
  title={Counting Hallucinations in Diffusion Models},
  author={Fu, Shuai and Zhou, Jian and Chen, Qi and Jing, Huang and Nguyen, Huy Anh and Liu, Xiaohan and Zeng, Zhixiong and Ma, Lin and Zhang, Quanshi and Wu, Qi},
  journal={arXiv preprint arXiv:2510.13080},
  year={2025}
}