Saurabh Hinduja, Shaun Canavan, Liza Jivnani, Sk Rahatul Jannat, V Sri Chakra Kumar
Published 2022-03-24Version 1
In this paper we describe our approach to the arousal and valence track of the 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW). We extracted facial features using OpenFace and used them to train a multiple output random forest regressor. Our approach performed comparable to the baseline approach.
Unifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis
Region Based Adversarial Synthesis of Facial Action Units
Recognizing Combinations of Facial Action Units with Different Intensity Using a Mixture of Hidden Markov Models and Neural Network
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