Recognition of Abnormal Events in Surveillance Videos using Weakly Supervised Dual-Encoder Models
Authors: name: Noam Tsfaty, name: Avishai Weizman, name: Liav Cohen, name: Moshe Tshuva, name: Yehudit Aperstein

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.