Research highlights

OneNet to solve inverse problems
ICCV 2017

Reflectance capture using mobile devices
ICCV 2017

Non-line-of-sight imaging using first-returning photons
CVPR 2017

Detecting spectral anomalies using computational imaging
ICCP 2017

High bit-depth projection
Optics Express 2016

Structured light using a 1D sensor
ECCV 2016

White balancing using flash photography
ICCP 2016

Shape and reflectance from two-bounce transients
ICCP 2016

Random features for sparse datasets
CVPR 2016

Cross-scale predictive dictionaries
ICIP 2016

FlatCam --- Thin, bare-sensor lens-free cameras
TCI 2017, Extreme Computational Imaging, 2015

Photometric stereo with small angular variations
ICCV 2015

Lab mission

Light often interacts with materials in complex, fascinating ways. Our research devises theories to model these interactions, build imaging architectures to sense them, and finally developing a deeper understanding of the world around us based on these interactions. We bring together ideas in signal and image processing, computational imaging, vision, machine learning, and compressive sensing to achieve this.

See our research