63 citations · 81 across the 5 of their papers we have counts for
5 papers
One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models
J. H. Rick Chang, Chun-Liang Li, Barnabas Poczos +2
While deep learning methods have achieved state-of-the-art performance in many challenging inverse problems like image inpainting and super-resolution, they invariably involve prob…
FPA-CS: Focal Plane Array-based Compressive Imaging in Short-wave Infrared
Huaijin Chen, M. Salman Asif, Aswin C. Sankaranarayanan +1
Cameras for imaging in short and mid-wave infrared spectra are significantly more expensive than their counterparts in visible imaging. As a result, high-resolution imaging in thos…
LiSens --- A Scalable Architecture for Video Compressive Sensing
Jian Wang, Mohit Gupta, Aswin C. Sankaranarayanan
The measurement rate of cameras that take spatially multiplexed measurements by using spatial light modulators (SLM) is often limited by the switching speed of the SLMs. This is es…
A Dictionary-based Approach for Estimating Shape and Spatially-Varying Reflectance
Zhuo Hui, Aswin C. Sankaranarayanan
We present a technique for estimating the shape and reflectance of an object in terms of its surface normals and spatially-varying BRDF. We assume that multiple images of the objec…
Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction
Joao F. C. Mota, Nikos Deligiannis, Aswin C. Sankaranarayanan +2
We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown suppo…