Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Facial expression recognition (FER) is an emerging and multifaceted research topic.
Applications of FER in healthcare, security, safe driving, and so forth have contributed to the …

We demonstrate that it is possible to perform face-related computer vision in the wild using
synthetic data alone. The community has long enjoyed the benefits of synthesizing training …

Research in automatic analysis of facial expressions mainly focuses on recognising the
seven basic ones. However, compound expressions are more diverse and represent the …

We focus on reconstructing high-fidelity radiance fields of human heads, capturing their
animations over time, and synthesizing re-renderings from novel viewpoints at arbitrary time …

With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

Multi-Task Learning has emerged as a methodology in which multiple tasks are jointly
learned by a shared learning algorithm, such as a DNN. MTL is based on the assumption …

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and propose a
novel algorithm that is able to predict elaborate riggable 3D face models from a single image …

The RAVDESS is a validated multimodal database of emotional speech and song. The
database is gender balanced consisting of 24 professional actors, vocalizing lexically …

Affect recognition based on subjects' facial expressions has been a topic of major research
in the attempt to generate machines that can understand the way subjects feel, act and react …