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+# Skeleton-Robustness-Benchmark(RobustBenchHAR)
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+RobustBenchHAR is a pytorch framework to boost and evaluate the adversarial robustness for Human skeletal behavior recognition. Official code for the paper:
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+> **[ICLR2025 TASAR: Transfer-based Attack on Skeletal Action Recognition](https://arxiv.org/abs/2409.02483)**
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+Key Features of RobustBenchHAR:
++ **The first large-scale benchmark for evaluating adversarial robustness in human Activity Recognition (HAR)**: RobustBenchHAR ensembles existing adversarial attacks including several types and fairly evaluates various attacks under the same setting.
++ **Evaluate the robustness of various models and datasets**: RobustBenchHAR provides a plug-and-play interface to verify the robustness of models on different data sets.
++ **A summary of transfer-based attacks and defenses**: RobustBenchHAR reviews multiple adversarial attacks and defenses, making it easy to get the whole picture of attacks for practitioners.
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+For a full tutorial, please visit our [github repository](https://github.com/yunfengdiao/Skeleton-Robustness-Benchmark)