3 papers
cs.CV2025
SHARDeg: A Benchmark for Skeletal Human Action Recognition in Degraded Scenarios
Simon Malzard, Nitish Mital, Richard Walters +3
Computer vision (CV) models for detection, prediction or classification tasks operate on video data-streams that are often degraded in the real world, due to deployment in real-tim…
cs.CV2025
Improving Object Detection by Modifying Synthetic Data with Explainable AI
Nitish Mital, Simon Malzard, Richard Walters +3
Limited real-world data severely impacts model performance in many computer vision domains, particularly for samples that are underrepresented in training. Synthetically generated…
cs.CV2025
2DSig-Detect: a semi-supervised framework for anomaly detection on image data using 2D-signatures
Xinheng Xie, Kureha Yamaguchi, Margaux Leblanc +4
The rapid advancement of machine learning technologies raises questions about the security of machine learning models, with respect to both training-time (poisoning) and test-time…