Sizhuo Ma

Sizhuo Ma

Research Scientist

Snap Research


I am a Research Scientist at Snap Research. My research interests lie in computer vision and computational imaging. I received my PhD in Computer Sciences at UW-Madison, advised by Professor Mohit Gupta.

My PhD work focuses on solving geometry, motion-related computer vision problems using novel computational cameras. For example, how can we accurately recover minuscule motion of objects? How can we take a clear, sharp image of a extremely dark and moving scene? I develop novel solutions to these problems using light field cameras, structured light and single-photon cameras.

Download my CV.

  • Computer Vision
  • Computational Photography
  • Computational Imaging
  • PhD in Computer Sciences, 2022

    University of Wisconsin-Madison

  • MS in Computer Sciences, 2016

    University of Wisconsin-Madison

  • BS in Computer Science, 2014

    Shanghai Jiao Tong University


May 2023: One paper accepted to SIGGRAPH 2023!

April 2023: One paper accepted to MobiCom 2023!

Februrary 2023: One paper accepted to CVPR 2023!

October 2022: One paper accepted to WACV 2023!

June 2022: I will attend CVPR 2022 in New Orleans, LA.

May 2022: I received 2022 Outstanding Graduate-Student Research Award! Thanks for everyone who has collaborated with me or supported my research.

February 2022: I joined Snap Research as a Research Scientist!

December 2021: I passed my PhD oral defense! Thanks everyone for their support!

December 2020: I received 2020 Snap Research Fellowship!

June 2020: Quanta Burst Photography was reported by UW-Madison News and EPFL News.

May 2020: Our paper Quanta Burst Photography was featured in SIGGRAPH Technical Papers highlights.


Seeing Photons in Color

Color filter and algorithm design for single-photon color imaging in low light
Seeing Photons in Color
QfaR: Location-Guided Scanning of Visual Codes from Long Distances

MobiCom 2023
A novel location-guided approach that extends the scanning distance of QR codes by 4x or more
QfaR: Location-Guided Scanning of Visual Codes from Long Distances
Energy-Efficient Adaptive 3D Sensing

CVPR 2023
Energy-efficient and eye-safe active 3D sensing that is adapted to the scene and application
Energy-Efficient Adaptive 3D Sensing
Burst Vision Using Single-Photon Cameras

WACV 2023
Exploring the capabilities of SPAD sensors for a wide gamut of real-world computer vision tasks including object detection, pose estimation, SLAM, text recognition and so on
Burst Vision Using Single-Photon Cameras
Single-Photon Structured Light

CVPR 2022
Structured light 3D imaging enabled at extreme speeds and challenging scenarios using single-photon cameras and digital micro-mirror devices.
Single-Photon Structured Light
Inertial Safety from Structured Light

ECCV 2020
A novel scene representation that enables fast detection of obstacles in scenarios involving camera or scene motion using single-shot structured light
Inertial Safety from Structured Light
Quanta Burst Photography

A computational imaging technique with single-photon cameras enables ultra-low light photography
Quanta Burst Photography
3D Scene Flow from 4D Light Field Gradients

ECCV 2018 oral presentation, selected for IJCV Special Issue on Best of ECCV
Recover high-precision dense scene flow from light fields
3D Scene Flow from 4D Light Field Gradients


(2023). Seeing Photons in Color. SIGGRAPH 2023.

PDF Project Video

(2023). QfaR: Location-Guided Scanning of Visual Codes from Long Distances. MobiCom 2023.


(2023). Energy-Efficient Adaptive 3D Sensing. CVPR 2023.

PDF Code Project Video

(2022). Burst Vision Using Single-Photon Cameras. WACV 2023.

PDF Project Video

(2022). Single-Photon Structured Light. CVPR 2022.

PDF Project Slides Video