3 citations · 4 across the 5 of their papers we have counts for
5 papers
Action Unit Detection with Region Adaptation, Multi-labeling Learning and Optimal Temporal Fusing
Wei Li, Farnaz Abitahi, Zhigang Zhu
Action Unit (AU) detection becomes essential for facial analysis. Many proposed approaches face challenging problems in dealing with the alignments of different face regions, in th…
EAC-Net: A Region-based Deep Enhancing and Cropping Approach for Facial Action Unit Detection
Wei Li, Farnaz Abtahi, Zhigang Zhu +1
In this paper, we propose a deep learning based approach for facial action unit detection by enhancing and cropping the regions of interest. The approach is implemented by adding t…
Learning and Fusing Multimodal Features from and for Multi-task Facial Computing
Wei Li, Zhigang Zhu
We propose a deep learning-based feature fusion approach for facial computing including face recognition as well as gender, race and age detection. Instead of training a single cla…
A Recursive Framework for Expression Recognition: From Web Images to Deep Models to Game Dataset
Wei Li, Christina Tsangouri, Farnaz Abtahi +1
In this paper, we propose a recursive framework to recognize facial expressions from images in real scenes. Unlike traditional approaches that typically focus on developing and ref…
Towards an "In-the-Wild" Emotion Dataset Using a Game-based Framework
Wei Li, Farnaz Abtahi, Christina Tsangouri +1
In order to create an "in-the-wild" dataset of facial emotions with large number of balanced samples, this paper proposes a game-based data collection framework. The framework main…