Search Results for author: Parham Aarabi

Found 12 papers, 3 papers with code

Deep Graphics Encoder for Real-Time Video Makeup Synthesis from Example

no code implementations12 May 2021 Robin Kips, Ruowei Jiang, Sileye Ba, Edmund Phung, Parham Aarabi, Pietro Gori, Matthieu Perrot, Isabelle Bloch

While makeup virtual-try-on is now widespread, parametrizing a computer graphics rendering engine for synthesizing images of a given cosmetics product remains a challenging task.

Virtual Try-on

Continuous Face Aging via Self-estimated Residual Age Embedding

no code implementations CVPR 2021 Zeqi Li, Ruowei Jiang, Parham Aarabi

In this work, we propose a unified network structure that embeds a linear age estimator into a GAN-based model, where the embedded age estimator is trained jointly with the encoder and decoder to estimate the age of a face image and provide a personalized target age embedding for age progression/regression.

Face Generation

Semantic Relation Preserving Knowledge Distillation for Image-to-Image Translation

no code implementations ECCV 2020 Zeqi Li, Ruowei Jiang, Parham Aarabi

Generative adversarial networks (GANs) have shown significant potential in modeling high dimensional distributions of image data, especially on image-to-image translation tasks.

Image-to-Image Translation Knowledge Distillation +1

LOHO: Latent Optimization of Hairstyles via Orthogonalization

1 code implementation CVPR 2021 Rohit Saha, Brendan Duke, Florian Shkurti, Graham W. Taylor, Parham Aarabi

Therefore, we propose Latent Optimization of Hairstyles via Orthogonalization (LOHO), an optimization-based approach using GAN inversion to infill missing hair structure details in latent space during hairstyle transfer.

GAN inversion SSIM

Nail Polish Try-On: Realtime Semantic Segmentation of Small Objects for Native and Browser Smartphone AR Applications

no code implementations5 Jun 2019 Brendan Duke, Abdalla Ahmed, Edmund Phung, Irina Kezele, Parham Aarabi

We also provide a postprocessing and rendering algorithm for nail polish try-on, which integrates with our semantic segmentation and fingernail base-tip direction predictions.

Semantic Segmentation

Lightweight Real-time Makeup Try-on in Mobile Browsers with Tiny CNN Models for Facial Tracking

no code implementations5 Jun 2019 TianXing Li, Zhi Yu, Edmund Phung, Brendan Duke, Irina Kezele, Parham Aarabi

Recent works on convolutional neural networks (CNNs) for facial alignment have demonstrated unprecedented accuracy on a variety of large, publicly available datasets.

Adversarial Attacks on Face Detectors using Neural Net based Constrained Optimization

no code implementations31 May 2018 Avishek Joey Bose, Parham Aarabi

Adversarial attacks involve adding, small, often imperceptible, perturbations to inputs with the goal of getting a machine learning model to misclassifying them.

Adversarial Attack Image Classification +1

Hybrid eye center localization using cascaded regression and hand-crafted model fitting

no code implementations7 Dec 2017 Alex Levinshtein, Edmund Phung, Parham Aarabi

At an average normalized error of e < 0. 05, the regressor trained on manually annotated data yields an accuracy of 95. 07% (BioID), 99. 27% (GI4E), and 95. 68% (TalkingFace).

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