Unified WorkStation 4 Video Anomaly Detection

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UWS4VAD is an attempt to unify common pratices in VAD methods, with support for both UCFC and XDV datasets, configured trough hydra for a modular and experimental pipeline. Includes feature extraction for both visual (trough timm models) and audio (trough HEAR-based models).~

Important

Looking for contributions/suggestions of any kind. If you have interest in the project, please dont hesitate to contact, will be more than grateful for such.

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Installation

conda env create -f environment.yml && conda activate uws4vad

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Usage

Basic overview of configuration setup

python main.py --help

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Acknowledgments

Gratzie to author's works that are either part of this project, served as inspiration or contributed to VAD. Refer to methods for a complete and updated list.

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Citation

Give a shout if used:

@misc{uws4vad,
author = {Zuble Barbas},
title = {A Unified WorkStation for Video Anomaly Detection.},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/zuble/uws4vad}},
year = {2024},
}