Search Results for author:
Found 2 papers, 0 papers with code
Frequency-Guided Multi-Level Human Action Anomaly Detection with Normalizing Flows
We introduce the task of human action anomaly detection (HAAD), which aims to identify anomalous motions in an unsupervised manner given only the pre-determined normal category of training action samples.
PMSSC: Parallelizable multi-subset based self-expressive model for subspace clustering
Subspace clustering methods which embrace a self-expressive model that represents each data point as a linear combination of other data points in the dataset provide powerful unsupervised learning techniques.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
