Video anomaly detection (VAD) has been extensively studied for static cameras but is much
more challenging in egocentric driving videos where the scenes are extremely dynamic …

Video anomaly detection (VAD) has been extensively studied. However, research on
egocentric traffic videos with dynamic scenes lacks large-scale benchmark datasets as well …

Identifying unusual driving behaviors exhibited by drivers during driving is essential for
understanding driver behavior and the underlying causes of crashes. Previous studies have …

Anomalous events detection in real-world video scenes is a challenging problem due to the
complexity of" anomaly" as well as the cluttered backgrounds, objects and motions in the …

Video anomaly detection (VAD) is a challenging computer vision task with many practical
applications. As anomalies are inherently ambiguous, it is essential for users to understand …

Anomaly detection in traffic videos has been recently gaining attention due to its importance
in intelligent transportation systems. Due to several factors such as weather, viewpoint …

Traffic anomaly detection of unsupervised videos has attracted great interests in computer
vision field, and this task is very challenging since the scarcity of data and scene diversities …

Recognizing abnormal events such as traffic violations and accidents in natural driving
scenes is essential for successful autonomous driving and advanced driver assistance …

Time-stamp aware anomaly detection in traffic videos is an essential task for the
advancement of intelligent transportation system. Anomaly detection in videos is a …

Activity detection has wide-reaching applications in video surveillance, sports, and behavior
analysis. The existing literature in activity detection has mainly focused on benchmarks like …