14 citations · 47 across the 22 of their papers we have counts for
8 papers · 1 filter
JoJoGAN: One Shot Face Stylization
Min Jin Chong, David Forsyth
A style mapper applies some fixed style to its input images (so, for example, taking faces to cartoons). This paper describes a simple procedure -- JoJoGAN -- to learn a style mapp…
StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN
Min Jin Chong, Hsin-Ying Lee, David Forsyth
Recently, StyleGAN has enabled various image manipulation and editing tasks thanks to the high-quality generation and the disentangled latent space. However, additional architectur…
DIVeR: Real-time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Rendering
Liwen Wu, Jae Yong Lee, Anand Bhattad +2
DIVeR builds on the key ideas of NeRF and its variants -- density models and volume rendering -- to learn 3D object models that can be rendered realistically from small numbers of…
On the Importance of Firth Bias Reduction in Few-Shot Classification
Saba Ghaffari, Ehsan Saleh, David Forsyth +1
Learning accurate classifiers for novel categories from very few examples, known as few-shot image classification, is a challenging task in statistical machine learning and compute…
LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part Hierarchies
Dominic Roberts, Ara Danielyan, Hang Chu +2
Generative models for 3D shapes represented by hierarchies of parts can generate realistic and diverse sets of outputs. However, existing models suffer from the key practical limit…
Retrieve in Style: Unsupervised Facial Feature Transfer and Retrieval
Min Jin Chong, Wen-Sheng Chu, Abhishek Kumar +1
We present Retrieve in Style (RIS), an unsupervised framework for facial feature transfer and retrieval on real images. Recent work shows capabilities of transferring local facial…