FlatCam is a thin form-factor lensless camera that consists of a coded mask placed on top of
a bare, conventional sensor array. Unlike a traditional, lens-based camera, where an image …

In this work we present a deep learning framework for video compressive sensing. The
proposed formulation enables recovery of video frames in a few seconds at significantly …

It has been over a decade since the first coded aperture video compressive sensing (CS)
system was reported. The underlying principle of this technology is to employ a high …

Video snapshot compressive imaging (SCI) aims to capture a sequence of video frames with
only a single shot of a 2D detector, whose backbones rest in optical modulation patterns …

Signal capture is at the forefront of perceiving and understanding the environment; thus,
imaging plays a pivotal role in mobile vision. Recent unprecedented progress in artificial …

Successive images of a scene are captured and then further processed to achieve the
moving object tracking. However, due to modulation rate limitations of the spatial light …

Current HDR acquisition techniques are based on either (i) fusing multibracketed, low
dynamic range (LDR) images,(ii) modifying existing hardware and capturing different …

Studies in biological vision have always been a great source of inspiration for design of
computer vision algorithms. In the past, several successful methods were designed with …

We build a compressive imaging system that can reconstruct high-speed videos of two fields-
of-view by capturing a single frame. A single digital micromirror device is employed to …

In this paper, we propose an encoder-decoder neural network model referred to as
DeepBinaryMask for video compressive sensing. In video compressive sensing one frame is …