43 citations · 132 across the 28 of their papers we have counts for
11 papers · 1 filter
Detection of Adversarial Attacks and Characterization of Adversarial Subspace
Mohammad Esmaeilpour, Patrick Cardinal, Alessandro Lameiras Koerich
Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propos…
Emotion Recognition with Spatial Attention and Temporal Softmax Pooling
Masih Aminbeidokhti, Marco Pedersoli, Patrick Cardinal +1
Video-based emotion recognition is a challenging task because it requires to distinguish the small deformations of the human face that represent emotions, while being invariant to…
Deep Weakly-Supervised Domain Adaptation for Pain Localization in Videos
R. Gnana Praveen, Eric Granger, Patrick Cardinal
Automatic pain assessment has an important potential diagnostic value for populations that are incapable of articulating their pain experiences. As one of the dominating nonverbal…
Universal Adversarial Audio Perturbations
Sajjad Abdoli, Luiz G. Hafemann, Jerome Rony +3
We demonstrate the existence of universal adversarial perturbations, which can fool a family of audio classification architectures, for both targeted and untargeted attack scenario…
Bag-of-Audio-Words based on Autoencoder Codebook for Continuous Emotion Prediction
Mohammed Senoussaoui, Patrick Cardinal, Alessandro Lameiras Koerich
In this paper we present a novel approach for extracting a Bag-of-Words (BoW) representation based on a Neural Network codebook. The conventional BoW model is based on a dictionary…
Multimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition
Juan D. S. Ortega, Mohammed Senoussaoui, Eric Granger +3
This paper presents a novel deep neural network (DNN) for multimodal fusion of audio, video and text modalities for emotion recognition. The proposed DNN architecture has independe…