iWarpGAN: Disentangling Identity and Style to Generate Synthetic Iris Images

S Yadav, A Ross - 2023 IEEE International Joint Conference on …, 2023 - ieeexplore.ieee.org
Generative Adversarial Networks (GANs) have shown success in approximating complex
distributions for synthetic image generation. However, current GAN-based methods for …

Facial expression: psychophysiological study

E Lyakso, O Frolova, Y Matveev - Handbook of Research on Deep …, 2021 - igi-global.com
The description of the results of five psychophysiological studies using automatic coding
facial expression in adults and children (from 4 to 16 years) in the FaceReader software …

Dispositionet: Disentangled pose and identity in semantic image manipulation

A Farshad, Y Yeganeh, H Dhamo, F Tombari… - arXiv preprint arXiv …, 2022 - arxiv.org
Graph representation of objects and their relations in a scene, known as a scene graph,
provides a precise and discernible interface to manipulate a scene by modifying the nodes …

Learning mixture of domain-specific experts via disentangled factors for autonomous driving

I Kim, J Lee, D Kim - Proceedings of the AAAI Conference on Artificial …, 2022 - ojs.aaai.org
Since human drivers only consider the driving-related factors that affect vehicle control
depending on the situation, they can drive safely even in diverse driving environments. To …

CtrlFaceNet: Framework for geometric-driven face image synthesis

B Zeno, I Kalinovskiy, Y Matveev, B Alkhatib - Pattern Recognition Letters, 2020 - Elsevier
In this work, we introduce a novel framework based on Generative Adversarial Networks to
control the pose, expression and facial features of a given face image using another face …

PFA-GAN: Pose face augmentation based on generative adversarial network

B Zeno, I Kalinovskiy, Y Matveev - Informatica, 2021 - content.iospress.com
In this work, we propose a novel framework based on Generative Adversarial Networks for
pose face augmentation (PFA-GAN). It enables a controlled pose synthesis of a new face …