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Official PyTorch Implementation of the IJCB 2023 Paper "Enhancing 3D-Air Signature by Pen Tip Tail Trajectory Awareness: Dataset and Featuring by Novel Spatio-temporal CNN"

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Benchmarking Air Signature Verifications on T3AAS-v1

Offical PyTorch Implementation of the IJCB 2023 Paper "Enhancing 3D-Air Signature by Pen Tip Tail Trajectory Awareness: Dataset and Featuring by Novel Spatio-temporal CNN" [Arxiv]

Dataset (T3AAS-v1)

Use this Form to request access to the T3AAS-v1 dataset.

Setup

Dependencies

Use environment.yml (with conda) or requirements.txt (with pip) to install dependencies.

Running experiments

All experiments are launched using main.py. To know the full specification of arguments that can be passed, execute:

python main.py --help

An example script is available in run.sh.

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Official PyTorch Implementation of the IJCB 2023 Paper "Enhancing 3D-Air Signature by Pen Tip Tail Trajectory Awareness: Dataset and Featuring by Novel Spatio-temporal CNN"

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