3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in environmental-sound-classification
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Use these libraries to find environmental-sound-classification models and implementations
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The experiments show that CrissCross either outperforms or achieves performances on par with the current state-of-the-art self-supervised methods on action recognition and action retrieval with UCF101 and HMDB51, as well as sound classification with ESC50 and DCASE.
Adding a benchmark result helps the community track progress.