no code implementations • 16 Jul 2022 • Antonio Barbalau, Radu Tudor Ionescu, Mariana-Iuliana Georgescu, Jacob Dueholm, Bharathkumar Ramachandra, Kamal Nasrollahi, Fahad Shahbaz Khan, Thomas B. Moeslund, Mubarak Shah
A self-supervised multi-task learning (SSMTL) framework for video anomaly detection was recently introduced in literature.
Ranked #2 on Anomaly Detection on CUHK Avenue
no code implementations • 8 Jul 2020 • Zexi Chen, Bharathkumar Ramachandra, Ranga Raju Vatsavai
Our experiments show that this new composite consistency regularization based semi-GAN significantly improves its performance and achieves new state-of-the-art performance among GAN-based SSL approaches.
1 code implementation • 20 Apr 2020 • Zexi Chen, Benjamin Dutton, Bharathkumar Ramachandra, Tianfu Wu, Ranga Raju Vatsavai
In MT, each data point is considered independent of other points during training; however, data points are likely to be close to each other in feature space if they share similar features.
no code implementations • 13 Apr 2020 • 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.
no code implementations • 24 Jan 2020 • Bharathkumar Ramachandra, Michael J. Jones, Ranga Raju Vatsavai
The learned distance function, which is not specific to the target video, is used to measure the distance between each video patch in the testing video and the video patches found in normal training video.
Ranked #18 on Anomaly Detection on CUHK Avenue
no code implementations • 18 Jun 2019 • Bharathkumar Ramachandra, Benjamin Dutton, Ranga Raju Vatsavai
We formulate three methods that use the data assigned to each tangent space to estimate the underlying bounded subspaces for which the tangent space is a faithful estimate of the manifold and offer thoughts on how this perspective is theoretically grounded in the manifold assumption.
no code implementations • 15 Feb 2019 • Bharathkumar Ramachandra, Michael Jones
Progress in video anomaly detection research is currently slowed by small datasets that lack a wide variety of activities as well as flawed evaluation criteria.
no code implementations • 16 Nov 2018 • Zexi Chen, Bharathkumar Ramachandra, Tianfu Wu, Ranga Raju Vatsavai
By doing this, our Relational LSTM is capable of capturing long and short-range spatio-temporal relations between objects in videos in a principled way.