In this paper, we present HoloNet, a well-designed Convolutional Neural Network (CNN)
architecture regarding our submissions to the video based sub-challenge of the Emotion …

State-of-the-art approaches for the previous emotion recognition in the wild challenges are
usually built on prevailing Convolutional Neural Networks (CNNs). Although there is clear …

Emotion recognition (ER) based on natural facial images/videos has been studied for some
years and considered a comparatively hot topic in the field of affective computing. However …

In the past three years, Emotion Recognition in the Wild (EmotiW) Grand Challenge has
drawn more and more attention due to its huge potential applications. In the fourth …

Group-level Emotion Recognition (GER) in the wild is a challenging task gaining lots of
attention. Most recent works utilized two channels of information, a channel involving only …

In this paper, we propose a multimodal deep learning architecture for emotion recognition in
video regarding our participation to the audio-video based sub-challenge of the Emotion …

Traditional techniques for emotion recognition have focused on the facial expression
analysis only, thus providing limited ability to encode context that comprehensively …

In this paper, we describe our work in the third Emotion Recognition in the Wild (EmotiW
2015) Challenge. For each video clip, we extract MSDF, LBP-TOP, HOG, LPQ-TOP and …

Emotion recognition from face images is a challenging task that gained interest in recent
years for its applications to business intelligence and social robotics. Researchers in …

We present a novel method for classifying emotions from static facial images. Our approach
leverages on the recent success of Convolutional Neural Networks (CNN) on face …