Search Results for author: Edmund Phung

Found 5 papers, 1 papers with code

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).

regression

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.

Segmentation 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.

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

Cannot find the paper you are looking for? You can Submit a new open access paper.