Datasetpublic

Haitao999/things-meg

THINGS-MEG This dataset is a processed version of THINGS-MEG, derived from the paper Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Prior (CVPR 2025). In this version, the MEG data is stored in float16 format, reducing the storage size by half. The original official dataset can be accessed from the OSF repository. Original official dataset: THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and… See the full description on the dataset page: https://huggingface.co/datasets/Haitao999/things-meg.

sourceHugging Faceupdated 6mo agoView on Hugging Face

0likes1.9kdownloads

Dataset Card

THINGS-MEG

This dataset is a processed version of THINGS-MEG, derived from the paper Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Prior (CVPR 2025). In this version, the MEG data is stored in float16 format, reducing the storage size by half. The original official dataset can be accessed from the [OSF repository]().

Original official dataset:

—THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior [THINGS-MEG]

Citation

bibtex

@InProceedings{Wu2025UBP,
    title = {Bridging the Vision-Brain Gap with an Uncertainty-Aware Blur Prior},
    author = {Wu, Haitao and Li, Qing and Zhang, Changqing and He, Zhen and Ying, Xiaomin},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year = {2025}
}

@article{hebart2023things,
  title={THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior},
  author={Hebart, Martin N and Contier, Oliver and Teichmann, Lina and Rockter, Adam H and Zheng, Charles Y and Kidder, Alexis and Corriveau, Anna and Vaziri-Pashkam, Maryam and Baker, Chris I},
  journal={Elife},
  volume={12},
  pages={e82580},
  year={2023},
  publisher={eLife Sciences Publications, Ltd}
}