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 …

Millimeter-wave (mmWave) radar, with its high resolution, sensitivity to micro-vibrations, and
adaptability to various environmental conditions, holds immense potential across multi …

Abstract Three-dimensional (3D) reconstruction from a single image is an ill-posed problem
with inherent ambiguities ie scale. Predicting a 3D scene from text description (s) is similarly …

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 …

While perspective is a well-studied topic in art, it is generally taken for granted in images.
However, for the recent wave of high-quality image synthesis methods such as latent …

We present a novel approach for metric dense depth estimation based on the fusion of a
single-view image and a sparse, noisy Radar point cloud. The direct fusion of …

It is widely believed that the dense supervision is better than the sparse supervision in the
field of depth completion, but the underlying reasons for this are rarely discussed. In this …

Depth completion aims to recover dense depth maps from sparse depth measurements. It is
a fundamental challenge in computer vision that is faced in numerous applications, such as …

Our research aims to generate robust, dense 3-D depth maps for robotics, especially
autonomous driving applications. Since cameras output 2-D images and active sensors …

Accurate depth cues are crucial for 3D perception tasks, and monocular depth estimation
networks are no longer sufficient for realistic scenarios. Currently, the most effective …