
Overview
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.
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- 3DCoMPaT Dataset
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- S3 bucket
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- arn:aws:s3:::3dcompat-dataset
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- us-west-1
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- aws s3 ls --no-sign-request s3://3dcompat-dataset/
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3DCoMPaT: Composition of Materials on Parts of 3D Things was accessed on DATE from https://registry.opendata.aws/3dcompat .