6 citations · 6 across the 3 of their papers we have counts for
6 papers
Real-time Virtual-Try-On from a Single Example Image through Deep Inverse Graphics and Learned Differentiable Renderers
Robin Kips, Ruowei Jiang, Sileye Ba +4
Augmented reality applications have rapidly spread across online platforms, allowing consumers to virtually try-on a variety of products, such as makeup, hair dying, or shoes. Howe…
LOHO: Latent Optimization of Hairstyles via Orthogonalization
Rohit Saha, Brendan Duke, Florian Shkurti +2
Hairstyle transfer is challenging due to hair structure differences in the source and target hair. Therefore, we propose Latent Optimization of Hairstyles via Orthogonalization (LO…
SSTVOS: Sparse Spatiotemporal Transformers for Video Object Segmentation
Brendan Duke, Abdalla Ahmed, Christian Wolf +2
In this paper we introduce a Transformer-based approach to video object segmentation (VOS). To address compounding error and scalability issues of prior work, we propose a scalable…
Lightweight Real-time Makeup Try-on in Mobile Browsers with Tiny CNN Models for Facial Tracking
TianXing Li, Zhi Yu, Edmund Phung +3
Recent works on convolutional neural networks (CNNs) for facial alignment have demonstrated unprecedented accuracy on a variety of large, publicly available datasets. However, the…
Nail Polish Try-On: Realtime Semantic Segmentation of Small Objects for Native and Browser Smartphone AR Applications
Brendan Duke, Abdalla Ahmed, Edmund Phung +2
We provide a system for semantic segmentation of small objects that enables nail polish try-on AR applications to run client-side in realtime in native and web mobile applications.…
Generalized Hadamard-Product Fusion Operators for Visual Question Answering
Brendan Duke, Graham W. Taylor
We propose a generalized class of multimodal fusion operators for the task of visual question answering (VQA). We identify generalizations of existing multimodal fusion operators b…