2 citations · 4 across the 7 of their papers we have counts for
5 papers · 1 filter
Privacy Aware Person Detection in Surveillance Data
Sander De Coninck, Sam Leroux, Pieter Simoens
Crowd management relies on inspection of surveillance video either by operators or by object detection models. These models are large, making it difficult to deploy them on resourc…
Intelligent Frame Selection as a Privacy-Friendlier Alternative to Face Recognition
Mattijs Baert, Sam Leroux, Pieter Simoens
The widespread deployment of surveillance cameras for facial recognition gives rise to many privacy concerns. This study proposes a privacy-friendly alternative to large scale faci…
Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video
Bo Li, Sam Leroux, Pieter Simoens
Automating the analysis of surveillance video footage is of great interest when urban environments or industrial sites are monitored by a large number of cameras. As anomalies are…
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification
Sam Leroux, Pavlo Molchanov, Pieter Simoens +3
Deep residual networks (ResNets) made a recent breakthrough in deep learning. The core idea of ResNets is to have shortcut connections between layers that allow the network to be m…
Lazy Evaluation of Convolutional Filters
Sam Leroux, Steven Bohez, Cedric De Boom +5
In this paper we propose a technique which avoids the evaluation of certain convolutional filters in a deep neural network. This allows to trade-off the accuracy of a deep neural n…