activity
20182022
most citedImplicit Neural Representations with Periodic Activation Functions

263 citations · 288 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV202225 cited

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…

cs.CV2021

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…

cs.CV2020

AutoInt: Automatic Integration for Fast Neural Volume Rendering

David B. Lindell, Julien N. P. Martel, Gordon Wetzstein

Numerical integration is a foundational technique in scientific computing and is at the core of many computer vision applications. Among these applications, neural volume rendering…

cs.CV2020263 cited

Implicit Neural Representations with Periodic Activation Functions

Vincent Sitzmann, Julien N. P. Martel, Alexander W. Bergman +2

Implicitly defined, continuous, differentiable signal representations parameterized by neural networks have emerged as a powerful paradigm, offering many possible benefits over con…

cs.CV2019

Keyhole Imaging: Non-Line-of-Sight Imaging and Tracking of Moving Objects Along a Single Optical Path

Christopher A. Metzler, David B. Lindell, Gordon Wetzstein

Non-line-of-sight (NLOS) imaging and tracking is an emerging technology that allows the shape or position of objects around corners or behind diffusers to be recovered from transie…

physics.app-ph2018

Sub-picosecond photon-efficient 3D imaging using single-photon sensors

Felix Heide, Steven Diamond, David B. Lindell +1

Active 3D imaging systems have broad applications across disciplines, including biological imaging, remote sensing and robotics. Applications in these domains require fast acquisit…