8 papers
Fourier Feature Pyramids for Physics-Informed Neural Networks
Brandon Zhao, Yixuan Wang, Jonathan T. Barron +3
We present an improved neural field architecture for solving partial differential equations (PDEs). Current physics-informed neural networks (PINNs) provide a flexible framework fo…
GR3EN: Generative Relighting for 3D Environments
Xiaoyan Xing, Philipp Henzler, Junhwa Hur +4
We present a method for relighting 3D reconstructions of large room-scale environments. Existing solutions for 3D scene relighting often require solving under-determined or ill-con…
ROGR: Relightable 3D Objects using Generative Relighting
Jiapeng Tang, Matthew Levine, Dor Verbin +5
We introduce ROGR, a novel approach that reconstructs a relightable 3D model of an object captured from multiple views, driven by a generative relighting model that simulates the e…
Bolt3D: Generating 3D Scenes in Seconds
Stanislaw Szymanowicz, Jason Y. Zhang, Pratul Srinivasan +6
We present a latent diffusion model for fast feed-forward 3D scene generation. Given one or more images, our model Bolt3D directly samples a 3D scene representation in less than se…
Revealing the 3D Cosmic Web through Gravitationally Constrained Neural Fields
Brandon Zhao, Aviad Levis, Liam Connor +2
Weak gravitational lensing is the slight distortion of galaxy shapes caused primarily by the gravitational effects of dark matter in the universe. In our work, we seek to invert th…
Generative Multiview Relighting for 3D Reconstruction under Extreme Illumination Variation
Hadi Alzayer, Philipp Henzler, Jonathan T. Barron +3
Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary acr…