It is a grand challenge for an imaging system to simultaneously obtain multi-dimensional
light field information, such as depth and polarization, of a scene for the accurate perception …

Segmentation of transparent objects is a hard, open problem in computer vision.
Transparent objects lack texture of their own, adopting instead the texture of scene …

We present a method for inferring dense depth from a camera image and a sparse noisy
radar point cloud. We first describe the mechanics behind mmWave radar point cloud …

This work introduces alternating latent topologies (ALTO) for high-fidelity reconstruction of
implicit 3D surfaces from noisy point clouds. Previous work identifies that the spatial …

Today single image deweathering is arguably more sensitive to the dataset type, rather than
the model. We introduce WeatherStream, an automatic pipeline capturing all real-world …

This paper makes a first attempt to bring the Shape from Polarization (SfP) problem to the
realm of deep learning. The previous state-of-the-art methods for SfP have been purely …

State-of-the-art solutions for Shape-from-Polarization (SfP) suffer from a speed-resolution
tradeoff: they either sacrifice the number of polarization angles measured or necessitate …

Polarization three-dimensional (3D) imaging technology has received extensive attention in
recent years because of its advantages of high accuracy, long detection distance, simplicity …

近年来偏振三维成像技术因具有精度高, 作用距离远和受杂散光影响小等特点得以蓬勃发展,
但利用目标反射光偏振特性进行法向量精确求解的问题一直没有真正得到解决 …

In this paper, we propose a hybrid depth imaging system in which a polarisation camera is
augmented by a second image from a standard digital camera. For this modest increase in …