activity
20172026
most citedFourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

1.2k citations · 2k across the 43 of their papers we have counts for

collaborators

48 papers

cs.CV2026

PointGT: Simultaneous Geometry and Texture Editing for Point-Based Representations

Yanshu Zhang, George Shramko, Pratul P. Srinivasan +1

We present PointGT, a point-based 3D representation that enables simultaneous editing of object geometry and appearance. Existing reconstruction and view synthesis techniques produ…

cs.LG2026

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…

cs.CV2026

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…

cs.CV2025

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…

astro-ph.CO2025

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…

cs.CV2025

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…