Hello, I'm Keunhong Park

I am a research scientist at Google, where I work on computer vision, graphics, and machine learning.

Previously, I was a Ph. D student at the University of Washington advised by Ali Farhadi and Steve Seitz.


News

  • May 2022: I have defended and will be joining Google as a research scientist.
  • Oct 2021: FiG-NeRF has been accepted to 3DV 2021.
  • Sep 2021: HyperNeRF has been accepted to SIGGRAPH Asia 2021. We have also released the code.
  • Jul 2021: Nerfies has been accepted to ICCV 2021 as an oral presentation.
  • Jun 2021: We present HyperNeRF, which uses ideas from level set methods to model topologically changing scenes.
  • Nov 2020: We present Nerfies, a way to turn casually captured selfie videos into free-viewpoint visualizations.
  • Jun 2020: We’ve released the code and data for LatentFusion.
  • Feb 2020: LatentFusion, our paper on zero-shot pose estimation, has been accepted to CVPR 2020.

Publications

HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields
FiG-NeRF: Figure Ground Neural Radiance Fields for 3D Object Category Modelling

FiG-NeRF: Figure Ground Neural Radiance Fields for 3D Object Category Modelling

3DV, 2021

Given a lot of images of an object category, you can train a NeRF to render them from novel views and interpolate between different instances.

Nerfies: Deformable Neural Radiance Fields

Nerfies: Deformable Neural Radiance Fields

ICCV, 2021 Oral Presentation

Learning deformation fields with a NeRF let's you reconstruct non-rigid scenes with high fidelity.

LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation
PhotoShape: Photorealistic Materials for Large-Scale Shape Collections

PhotoShape: Photorealistic Materials for Large-Scale Shape Collections

SIGGRAPH Asia, 2018 Journal Cover

By pairing large collections of images, 3D models, and materials, you can create thousands of photorealistic 3D models fully automatically.