activity
20182022
most citedRegistration-free Face-SSD: Single shot analysis of smiles, facial attributes, and affect in the wild

51 citations · 81 across the 9 of their papers we have counts for

collaborators

14 papers

cs.LG20229 cited

GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge Features

Siyang Song, Yuxin Song, Cheng Luo +7

Graph is powerful for representing various types of real-world data. The topology (edges' presence) and edges' features of a graph decides the message passing mechanism among verti…

cs.CV2022

The Effect of Model Compression on Fairness in Facial Expression Recognition

Samuil Stoychev, Hatice Gunes

Deep neural networks have proved hugely successful, achieving human-like performance on a variety of tasks. However, they are also computationally expensive, which has motivated th…

cs.CV20213 cited

Learning Graph Representation of Person-specific Cognitive Processes from Audio-visual Behaviours for Automatic Personality Recognition

Siyang Song, Zilong Shao, Shashank Jaiswal +3

This approach builds on two following findings in cognitive science: (i) human cognition partially determines expressed behaviour and is directly linked to true personality traits;…

cs.CV2021

Toward Affective XAI: Facial Affect Analysis for Understanding Explainable Human-AI Interactions

Luke Guerdan, Alex Raymond, Hatice Gunes

As machine learning approaches are increasingly used to augment human decision-making, eXplainable Artificial Intelligence (XAI) research has explored methods for communicating sys…

cs.CV20216 cited

Towards Fair Affective Robotics: Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition

Ozgur Kara, Nikhil Churamani, Hatice Gunes

As affective robots become integral in human life, these agents must be able to fairly evaluate human affective expressions without discriminating against specific demographic grou…

cs.CV20202 cited

Spatio-Temporal Analysis of Facial Actions using Lifecycle-Aware Capsule Networks

Nikhil Churamani, Sinan Kalkan, Hatice Gunes

Most state-of-the-art approaches for Facial Action Unit (AU) detection rely upon evaluating facial expressions from static frames, encoding a snapshot of heightened facial activity…