7 citations · 18 across the 8 of their papers we have counts for
8 papers
SSMTL++: Revisiting Self-Supervised Multi-Task Learning for Video Anomaly Detection
Antonio Barbalau, Radu Tudor Ionescu, Mariana-Iuliana Georgescu +6
A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was recently introduced in literature. Due to its highly accurate results, the method attracted…
Consistency Regularization with Generative Adversarial Networks for Semi-Supervised Learning
Zexi Chen, Bharathkumar Ramachandra, Ranga Raju Vatsavai
Generative Adversarial Networks (GANs) based semi-supervised learning (SSL) approaches are shown to improve classification performance by utilizing a large number of unlabeled samp…
Local Clustering with Mean Teacher for Semi-supervised Learning
Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra +2
The Mean Teacher (MT) model of Tarvainen and Valpola has shown favorable performance on several semi-supervised benchmark datasets. MT maintains a teacher model's weights as the ex…
A Survey of Single-Scene Video Anomaly Detection
Bharathkumar Ramachandra, Michael J. Jones, Ranga Raju Vatsavai
This survey article summarizes research trends on the topic of anomaly detection in video feeds of a single scene. We discuss the various problem formulations, publicly available d…
Learning a distance function with a Siamese network to localize anomalies in videos
Bharathkumar Ramachandra, Michael J. Jones, Ranga Raju Vatsavai
This work introduces a new approach to localize anomalies in surveillance video. The main novelty is the idea of using a Siamese convolutional neural network (CNN) to learn a dista…
Estimating a Manifold from a Tangent Bundle Learner
Bharathkumar Ramachandra, Benjamin Dutton, Ranga Raju Vatsavai
Manifold hypotheses are typically used for tasks such as dimensionality reduction, interpolation, or improving classification performance. In the less common problem of manifold es…