Recognition of Abnormal Events in Surveillance Videos using Weakly Supervised Dual-Encoder Models

Noam Tsfaty, avishai, Liav Cohen, Moshe Tshuva, Yehudit Aperstein

Recognition of Abnormal Events in Surveillance Videos using Weakly Supervised Dual-Encoder Models: 1 upvotes on Hugging Face Daily Papers, #29 of 32 papers on 2025-12-01. Day-by-day upvote history.

We address the challenge of detecting rare and diverse anomalies in surveillance videos using only video-level supervision. Our dual-backbone framework combines convolutional and transformer representations through top-k pooling, achieving 90.7% area under the curve (AUC) on the UCF-Crime dataset.

Paper page on Hugging Face · arXiv

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