--- license: cc0-1.0 --- # [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} } ```