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3DCoMPaT: Composition of Materials on Parts of 3D Things

computer vision machine learning

Description

3D CoMPaT is a richly annotated large-scale dataset of rendered compositions of Materials on Parts of thousands of unique 3D Models. This dataset primarily focuses on stylizing 3D shapes at part-level with compatible materials. Each object with the applied part-material compositions is rendered from four equally spaced views as well as four randomized views. We introduce a new task, called Grounded CoMPaT Recognition (GCR), to collectively recognize and ground compositions of materials on parts of 3D objects. We present two variations of this task and adapt state-of-art 2D/3D deep learning methods to solve the problem as baselines for future research. We hope our work will help ease future research on compositional 3D Vision.

Update Frequency

Continually improving 3D annotations and renderings

License

https://3dcompat-dataset.org/LICENSE

Documentation

https://3dcompat-dataset.org/

Managed By

See all datasets managed by Vision-CAIR, CEMSE, KAUST.

Contact

mohamed.elhoseiny@kaust.edu.sa, yuchen.li@kaust.edu.sa

How to Cite

3DCoMPaT: Composition of Materials on Parts of 3D Things was accessed on DATE from https://registry.opendata.aws/3dcompat.

Usage Examples

Publications

Resources on AWS

  • Description
    3DCoMPaT Dataset
    Resource type
    S3 Bucket
    Amazon Resource Name (ARN)
    arn:aws:s3:::3dcompat-dataset
    AWS Region
    us-west-1
    AWS CLI Access (No AWS account required)
    aws s3 ls --no-sign-request s3://3dcompat-dataset/
    Explore
    Website

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