David Lindell

About

I'm a fourth-year Ph.D. student at Stanford University in the Computational Imaging Lab. My work is at the intersection of optimization, machine learning, optics, and hardware. Along these lines I've been developing next-generation computational LIDAR systems and algorithms for imaging around corners. I'm generally interested in problems in 3D imaging, inverse scattering, optimization, and computer vision, with a goal of developing computational methods to push the boundaries of current imaging capabilities. My work is relevant to a broad range of applications including autonomous vehicle navigation, medical imaging, remote sensing, and robotic vision.

News

Jun 2020

May 2020

I’m co-chairing the 9th annual Computational Cameras and Displays workshop at CVPR 2020 with Achuta Kadambi and Katie Bouman.

Mar 2020

Update: My talk is featured on the TED website with nearly a quarter million views!

Jan 2020

My TedxBeaconStreet talk on “a camera to see around corners” is up on YouTube!

May 2019

Two papers accepted! Acoustic Non-Line-of-Sight Imaging was accepted as an oral to CVPR, and Wave-Based Non-Line-of-Sight Imaging Using Fast f-k Migration was accepted to SIGGRAPH.

Jun 2018

I’m interning at the Intelligent Systems Lab at Intel this summer with Vladlen Koltun.

Mar 2018

Our paper on Seeing around corners was published in Nature!

Publications

Non-line-of-sight surface reconstruction using the directional light-cone transform

CVPR 2020 (oral)

Sean I. Young, David B. Lindell, Bernd Girod, David Taubman, Gordon Wetzstein

Deep adaptive LIDAR: End-to-end optimization of sampling and depth completion at low sampling rates

ICCP 2020

Alexander W. Bergman, David B. Lindell, Gordon Wetzstein

SPADnet: Deep RGB-SPAD sensor fusion assisted by monocular depth estimation

Optics Express (2020)

Zhanghao Sun, David B. Lindell, Olav Solgaard, Gordon Wetzstein

Wave-based non-line-of-sight imaging using fast f–k migration

SIGGRAPH 2019

David B. Lindell, Matthew O'Toole, Gordon Wetzstein

Non-line-of-sight imaging with partial occluders and surface normals

ACM Transactions on Graphics 2019

Felix Heide, Matthew O"Toole, Kai Zang, David B. Lindell, Steven Diamond, Gordon Wetzstein

Acoustic non-line-of-sight imaging

CVPR 2019 (oral)

David B. Lindell, Gordon Wetzstein, Vladlen Koltun

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

Scientific Report (2018)

Felix Heide, Steven Diamond, David B. Lindell, Gordon Wetzstein

Single-photon 3D imaging with deep sensor fusion

SIGGRAPH 2018

David B. Lindell, Matthew O'Toole, Gordon Wetzstein

Towards transient imaging at interactive rates with single-photon detectors

ICCP 2018

David B. Lindell, Matthew O'Toole, Gordon Wetzstein

Confocal non-line-of-sight imaging based on the light-cone transform

Nature (2018)

Matthew O'Toole, David B. Lindell, Gordon Wetzstein

Reconstructing transient images from single-photon sensors

CVPR 2017 (Spotlight)

Matthew O'Toole, Felix Heide, David B. Lindell, Kai Zang, Steven Diamond, Gordon Wetzstein

High-resolution soil moisture retrieval with ASCAT

IEEE Geoscience and Remote Sensing Letters (2016)

David B.Lindell and David Long

Multiyear Arctic ice classification using ASCAT and SSMIS

Remote Sensing (2016)

David B. Lindell and David Long

Multiyear Arctic ice classification using OSCAT and QuikSCAT

IEEE Transactions on Geoscience and Remote Sensing (2015)

David B. Lindell and David Long

Education

  • 2016 – Present

    Stanford University

    Ph.D. Electrical Engineering

  • 2015 – 2016

    Brigham Young University

    M.S. Electrical Engineering

  • 2009 – 2015

    Brigham Young University

    B.S. Electrical Engineering

Invited Talks

Nov 2019

TEDxBeaconStreet 2019


A camera to see around corners

Nov 2019

Boston University Center for Information & Systems Engineering


Computational imaging with single-photon detectors

Nov 2019

MIT Research Laboratory of Electronics


Efficient confocal non-line-of-sight imaging

Sep 2019

Berkeley Center for Computational Imaging


Computational imaging with single-photon detectors

May 2019

Silicon Valley ACM SIGGRAPH Chapter


Computational single-photon imaging

May 2019

Stanford Center for Image Systems Engineering


Computational imaging with single-photon detectors

Jan 2019

Carnegie Mellon University Graphics Lab


Computational single-photon imaging