31 citations · 65 across the 8 of their papers we have counts for
8 papers
RMES: Real-Time Micro-Expression Spotting Using Phase From Riesz Pyramid
Yini Fang, Didan Deng, Liang Wu +2
Micro-expressions (MEs) are involuntary and subtle facial expressions that are thought to reveal feelings people are trying to hide. ME spotting detects the temporal intervals cont…
Multiple Emotion Descriptors Estimation at the ABAW3 Challenge
Didan Deng
To describe complex emotional states, psychologists have proposed multiple emotion descriptors: sparse descriptors like facial action units; continuous descriptors like valence and…
Iterative Distillation for Better Uncertainty Estimates in Multitask Emotion Recognition
Didan Deng, Liang Wu, Bertram E. Shi
When recognizing emotions, subtle nuances in displays of emotion generate ambiguity or uncertainty in emotion perception. Emotion uncertainty has been previously interpreted as int…
Individual risk profiling for portable devices using a neural network to process the cognitive reactions and the emotional responses to a multivariate situational risk assessment
Frederic Jumelle, Kelvin So, Didan Deng
In this paper, we are presenting a novel method and system for neuropsychological performance testing that can establish a link between cognition and emotion. It comprises a portab…
Functional neural network for decision processing, a racing network of programmable neurons with fuzzy logic where the target operating model relies on the network itself
Frederic Jumelle, Kelvin So, Didan Deng
In this paper, we are introducing a novel model of artificial intelligence, the functional neural network for modeling of human decision-making processes. This neural network is co…
Multitask Emotion Recognition with Incomplete Labels
Didan Deng, Zhaokang Chen, Bertram E. Shi
We train a unified model to perform three tasks: facial action unit detection, expression classification, and valence-arousal estimation. We address two main challenges of learning…
MIMAMO Net: Integrating Micro- and Macro-motion for Video Emotion Recognition
Didan Deng, Zhaokang Chen, Yuqian Zhou +1
Spatial-temporal feature learning is of vital importance for video emotion recognition. Previous deep network structures often focused on macro-motion which extends over long time…
Multimodal Utterance-level Affect Analysis using Visual, Audio and Text Features
Didan Deng, Yuqian Zhou, Jimin Pi +1
The integration of information across multiple modalities and across time is a promising way to enhance the emotion recognition performance of affective systems. Much previous work…