263 citations · 397 across the 10 of their papers we have counts for
5 papers · 1 filter
Instant Continual Learning of Neural Radiance Fields
Ryan Po, Zhengyang Dong, Alexander W. Bergman +1
Neural radiance fields (NeRFs) have emerged as an effective method for novel-view synthesis and 3D scene reconstruction. However, conventional training methods require access to al…
Efficient 3D Articulated Human Generation with Layered Surface Volumes
Yinghao Xu, Wang Yifan, Alexander W. Bergman +3
Access to high-quality and diverse 3D articulated digital human assets is crucial in various applications, ranging from virtual reality to social platforms. Generative approaches,…
Articulated 3D Head Avatar Generation using Text-to-Image Diffusion Models
Alexander W. Bergman, Wang Yifan, Gordon Wetzstein
The ability to generate diverse 3D articulated head avatars is vital to a plethora of applications, including augmented reality, cinematography, and education. Recent work on text-…
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…
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…