92 citations · 122 across the 4 of their papers we have counts for
5 papers · 1 filter
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…
3D GAN Inversion for Controllable Portrait Image Animation
Connor Z. Lin, David B. Lindell, Eric R. Chan +1
Millions of images of human faces are captured every single day; but these photographs portray the likeness of an individual with a fixed pose, expression, and appearance. Portrait…
ACORN: Adaptive Coordinate Networks for Neural Scene Representation
Julien N. P. Martel, David B. Lindell, Connor Z. Lin +3
Neural representations have emerged as a new paradigm for applications in rendering, imaging, geometric modeling, and simulation. Compared to traditional representations such as me…
pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesis
Eric R. Chan, Marco Monteiro, Petr Kellnhofer +2
We have witnessed rapid progress on 3D-aware image synthesis, leveraging recent advances in generative visual models and neural rendering. Existing approaches however fall short in…
MetaSDF: Meta-learning Signed Distance Functions
Vincent Sitzmann, Eric R. Chan, Richard Tucker +2
Neural implicit shape representations are an emerging paradigm that offers many potential benefits over conventional discrete representations, including memory efficiency at a high…