You are holding in your hands… oh, come on, who holds books like this in their hands
anymore? Anyway, you are reading this, and it means that I have managed to release one of …

In late fusion, each modality is processed in a separate unimodal Convolutional Neural
Network (CNN) stream and the scores of each modality are fused at the end. Due to its …

Abstract Domain shift is unavoidable in real-world applications of object detection. For
example, in self-driving cars, the target domain consists of unconstrained road environments …

To train deep learning models for vision-based action recognition of elders' daily activities,
we need large-scale activity datasets acquired under various daily living environments and …

We present an autoencoder-based semi-supervised approach to classify perceived human
emotions from walking styles obtained from videos or motion-captured data and represented …

The world's elderly population continues to grow at an unprecedented rate, creating a need
to monitor the safety of an aging population. One of the current problems is accurately …

Recognizing human actions is a core challenge for autonomous systems as they directly
share the same space with humans. Systems must be able to recognize and assess human …

This paper investigates a new attack method to gait recognition systems. Different from
typical spoofing attacks that require impostors to mimic certain clothing or walking styles, it …

We present a data-driven deep neural algorithm for detecting deceptive walking behavior
using nonverbal cues like gaits and gestures. We conducted an elaborate user study, where …

Instance-level object re-identification is a fundamental computer vision task, with
applications from image retrieval to intelligent monitoring and fraud detection. In this work …