|
--- |
|
license: apache-2.0 |
|
--- |
|
|
|
# [ECCV 2024] MinD-3D: Reconstruct High-quality 3D objects in Human Brain |
|
|
|
[![ArXiv](https://img.shields.io/badge/ArXiv-2312.07485-b31b1b.svg?logo=arXiv)](https://arxiv.org/abs/2312.07485) |
|
[![Github](https://img.shields.io/badge/Github-MinD_3D-blue.svg?logo=Github)](https://github.com/JianxGao/MinD-3D) |
|
|
|
## Overview |
|
MinD-3D aims to reconstruct high-quality 3D objects based on fMRI data. |
|
|
|
## Repository Structure |
|
- **annotations**: Contains metadata and annotations related to the fMRI data for each subject. |
|
- **sub-00xx**: Each folder corresponds to a specific subject and includes their respective raw and processed fMRI data. |
|
- **stimuli.zip**: A ZIP archive of all videos shown to subjects during the fMRI scans. This file includes the stimuli used across different sessions and is critical for reproducibility of the study findings. |
|
- **camera_pose.zip**: The camera pose for each frame in the videos (each containing 192 frames) in the stimuli. |
|
|
|
## Data Description |
|
- **raw_data**: Raw fMRI data collected directly from the imaging machine. |
|
- **npy_data**: Processed data. We utilized fMRIPrep and the methodologies described in our paper to derive and store the data in NumPy format (.npy). |
|
|
|
|
|
## Citation |
|
|
|
If you find our paper useful for your research and applications, please cite using this BibTeX: |
|
|
|
``` |
|
@misc{gao2023mind3d, |
|
title={MinD-3D: Reconstruct High-quality 3D objects in Human Brain}, |
|
author={Jianxiong Gao and Yuqian Fu and Yun Wang and Xuelin Qian and Jianfeng Feng and Yanwei Fu}, |
|
year={2023}, |
|
eprint={2312.07485}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CV} |
|
} |
|
``` |