Find the Leak, Fix the Split: Cluster-Based Method to Prevent Leakage in Video-Derived Datasets
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866912841464807424 |
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| author | Glazner, Noam Tsfaty, Noam Shalev, Sharon Weizman, Avishai |
| author_facet | Glazner, Noam Tsfaty, Noam Shalev, Sharon Weizman, Avishai |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13944 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Find the Leak, Fix the Split: Cluster-Based Method to Prevent Leakage in Video-Derived Datasets Glazner, Noam Tsfaty, Noam Shalev, Sharon Weizman, Avishai Computer Vision and Pattern Recognition 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. |
| title | Find the Leak, Fix the Split: Cluster-Based Method to Prevent Leakage in Video-Derived Datasets |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2511.13944 |