The emerging field of compressed sensing has potentially powerful implications for the
design of optical imaging devices. In particular, compressed sensing theory suggests that …

This state of the art report covers reconstruction methods for transparent and specular
objects or phenomena. While the 3D acquisition of opaque surfaces with Lambertian …

In this paper, we propose a robust visual tracking method by casting tracking as a sparse
approximation problem in a particle filter framework. In this framework, occlusion, noise, and …

In this paper we propose a robust visual tracking method by casting tracking as a sparse
approximation problem in a particle filter framework. In this framework, occlusion, corruption …

High-fidelity reconstruction of dynamic fluids from sparse multiview RGB videos remains a
formidable challenge, due to the complexity of the underlying physics as well as the severe …

We study recovering fluid density and velocity from sparse multiview videos. Existing neural
dynamic reconstruction methods predominantly rely on optical flows; therefore, they cannot …

Programmable coding of light between a source and a sensor has led to several important
results in computational illumination, imaging and display. Little is known, however, about …

The sparse representation has been widely used in many areas and utilized for visual
tracking. Tracking with sparse representation is formulated as searching for samples with …

Translucent materials are ubiquitous, and simulating their appearance requires accurate
physical parameters. However, physically-accurate parameters for scattering materials are …

This work focuses on a slice through the field-Computer Vision Metrics–from the view of
feature description metrics, or how to describe, compute and design the macro-features and …