Find the Leak, Fix the Split: Cluster-Based Method to Prevent Leakage in Video-Derived Datasets
Abstract
A cluster-based frame selection strategy groups visually similar frames to create more representative and balanced dataset partitions, reducing information leakage in video-derived frames datasets.
We propose a cluster-based frame selection strategy to mitigate information leakage in video-derived frames datasets. By grouping visually similar frames before splitting into training, validation, and test sets, the method produces more representative, balanced, and reliable dataset partitions.
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We propose a cluster-based frame selection strategy to mitigate information leakage in video-derived frames datasets. By grouping visually similar frames before splitting into training, validation, and test sets, the method produces more representative, balanced, and reliable dataset partitions.
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