CLIP-TSA: CLIP-Assisted Temporal Self-Attention for Weakly-Supervised Video Anomaly Detection

1 code implementation • 9 Dec 2022 • Hyekang Kevin Joo, Khoa Vo, Kashu Yamazaki, Ngan Le

Video anomaly detection (VAD) -- commonly formulated as a multiple-instance learning problem in a weakly-supervised manner due to its labor-intensive nature -- is a challenging problem in video surveillance where the frames of anomaly need to be localized in an untrimmed video.

Anomaly Detection Multiple Instance Learning +1