Search Results for author:
Found 6 papers, 2 papers with code
Towards mitigating uncann(eye)ness in face swaps via gaze-centric loss terms
We additionally propose a novel loss equation for the training of face swapping models, leveraging a pretrained gaze estimation network to directly improve representation of the eyes.
Introducing Explicit Gaze Constraints to Face Swapping
We find all methods to significantly benefit gaze in resulting face swaps.
Practical Digital Disguises: Leveraging Face Swaps to Protect Patient Privacy
With rapid advancements in image generation technology, face swapping for privacy protection has emerged as an active area of research.
Learning Oculomotor Behaviors from Scanpath
Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task.
Sparsely Grouped Input Variables for Neural Networks
In genomic analysis, biomarker discovery, image recognition, and other systems involving machine learning, input variables can often be organized into different groups by their source or semantic category.
A Facial Affect Analysis System for Autism Spectrum Disorder
In this paper, we introduce an end-to-end machine learning-based system for classifying autism spectrum disorder (ASD) using facial attributes such as expressions, action units, arousal, and valence.
