Publications (6)
Towards Graph-Based Privacy-Preserving Federated Learning: ModelNet -- A ResNet-based Model Classification Dataset
Abhisek Ray, Lukas Esterle
Federated Learning (FL) has emerged as a powerful paradigm for training machine learning models across distributed data sources while preserving data locality. However, the privacy…
Only Whats Necessary: Pareto Optimal Data Minimization for Privacy Preserving Video Anomaly Detection
Nazia Aslam, Abhisek Ray, Thomas B. Moeslund +1
Video anomaly detection (VAD) systems are increasingly deployed in safety critical environments and require a large amount of data for accurate detection. However, such data may co…
CFAT: Unleashing TriangularWindows for Image Super-resolution
Abhisek Ray, Gaurav Kumar, Maheshkumar H. Kolekar
Transformer-based models have revolutionized the field of image super-resolution (SR) by harnessing their inherent ability to capture complex contextual features. The overlapping r…
Autoregressive Adaptive Hypergraph Transformer for Skeleton-based Activity Recognition
Abhisek Ray, Ayush Raj, Maheshkumar H. Kolekar
Extracting multiscale contextual information and higher-order correlations among skeleton sequences using Graph Convolutional Networks (GCNs) alone is inadequate for effective acti…
Shapley Neuron Values for Continual Learning: Which Neurons Matter Most?
Mohammad Ali Vahedifar, Abhisek Ray, Qi Zhang
Continual learning enables neural networks to learn tasks sequentially without forgetting previously acquired knowledge. However, neural networks suffer from catastrophic forgettin…
From Pixels to Privacy: Temporally Consistent Video Anonymization via Token Pruning for Privacy Preserving Action Recognition
Nazia Aslam, Abhisek Ray, Joakim Bruslund Haurum +2
Recent advances in large-scale video models have significantly improved video understanding across domains such as surveillance, healthcare, and entertainment. However, these model…