2021
Weakly Supervised Temporal Anomaly Segmentation With Dynamic Time Warping
ICCV 2021poster
Most recent studies on detecting and localizing temporal anomalies have mainly employed deep neural networks to learn the normal patterns of temporal data in an unsupervised manner. Unlike them, the goal of our work is to fully utilize instance-level (or weak) anomaly labels, which only indicate whe…