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Dataset Preview

GeoGen Dataset

The GeoGen dataset is a comprehensive collection of over 70,000 synthetic face images designed for advanced 3D geometry reconstruction research.

The dataset is essential for training deep learning models that are geared towards high-fidelity 3D facial geometry reconstruction.

This dataset was introduced in our paper titled GeoGen: Geometry-Aware Generative Modeling via Signed Distance Functions.

The dataset contains:

  • The dataset comprises 70,000 images distributed across 10,000 identities, with each identity represented by 7 unique images. These images are captured from various camera angles spanning a full 360-degree view to enhance the diversity and comprehensiveness of the dataset. The dataset includes the camera extrinsics and intrinsics in json format.

The GeoGen dataset can be used for non-commercial research, and is licensed under the license found in LICENSE.

Downloading the Dataset

For convenience the images dataset is split into 7 parts and the last part contains the metadata with the camera parameters which can be downloaded here:

7 images per identity

Camera parameters:

Dataset Layout

The GeoGen dataset contains cropped color images in the following layout. For the camera parameters the average focal lenght is 50 and the sensor width is 36.

subj_id_n
├── 0.png                 # First rendered image of subject subj_id_n
├── 1.png                 # Second rendered image of subject subj_id_n
...
├── k.png                 # k+1 rendered image of subject subj_id_n

metadata_id_n_jsom                      # The extrinsics and intrinsics are in their respective metadata.json files in the following layout.

├── name of the subject                 # Corresponding name image from subj_id_n
├── cameras                             # Camera parameters of image from subj_id_n

Disclaimer

Some of our rendered faces may be close in appearance to the faces of real people. Any such similarity is naturally unintentional, as it would be in a dataset of real images, where people may appear similar to others unknown to them.

Citation

If you use the GeoGen dataset in your work, please cite the following paper:

@inproceedings{esposito2024geogen,
    author = {Esposito, Salvatore and Xu, Qingshan and Kania, Kacper and Hewitt, Charlie and Mariotti, Octave and Petikam, Lohit and Valentin, Julien and Onken, Arno and Mac Aodha, Oisin},
    title = {GeoGen: Geometry-Aware Generative Modeling via Signed Distance Functions},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month = {June},
    year = {2024},
    pages = {7479-7488}
}

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