92 citations · 259 across the 13 of their papers we have counts for
13 papers
Single-Shot Implicit Morphable Faces with Consistent Texture Parameterization
Connor Z. Lin, Koki Nagano, Jan Kautz +5
There is a growing demand for the accessible creation of high-quality 3D avatars that are animatable and customizable. Although 3D morphable models provide intuitive control for ed…
Real-Time Radiance Fields for Single-Image Portrait View Synthesis
Alex Trevithick, Matthew Chan, Michael Stengel +7
We present a one-shot method to infer and render a photorealistic 3D representation from a single unposed image (e.g., face portrait) in real-time. Given a single RGB input, our im…
Generative Novel View Synthesis with 3D-Aware Diffusion Models
Eric R. Chan, Koki Nagano, Matthew A. Chan +7
We present a diffusion-based model for 3D-aware generative novel view synthesis from as few as a single input image. Our model samples from the distribution of possible renderings…
Learning Object-Centric Neural Scattering Functions for Free-Viewpoint Relighting and Scene Composition
Hong-Xing Yu, Michelle Guo, Alireza Fathi +5
Photorealistic object appearance modeling from 2D images is a constant topic in vision and graphics. While neural implicit methods (such as Neural Radiance Fields) have shown high-…
Diffusion in the Dark: A Diffusion Model for Low-Light Text Recognition
Cindy M. Nguyen, Eric R. Chan, Alexander W. Bergman +1
Capturing images is a key part of automation for high-level tasks such as scene text recognition. Low-light conditions pose a challenge for high-level perception stacks, which are…
3D Neural Field Generation using Triplane Diffusion
J. Ryan Shue, Eric Ryan Chan, Ryan Po +3
Diffusion models have emerged as the state-of-the-art for image generation, among other tasks. Here, we present an efficient diffusion-based model for 3D-aware generation of neural…