In current decades, significant advancements in robotics engineering and autonomous
vehicles have improved the requirement for precise depth measurements. Depth estimation …

Depth estimation and 3D object detection are critical for scene understanding but remain
challenging to perform with a single image due to the loss of 3D information during image …

Monocular depth estimation remains a challenging problem, despite significant advances in
neural network architectures that leverage pictorial depth cues alone. Inspired by depth from …

Depth estimation is critical interest for scene understanding and accurate 3D reconstruction.
Most recent approaches with deep learning exploit geometrical structures of standard sharp …

Lens design is of paramount importance in the evolving world of technology, where
compactness and high optical performance are a necessity, ranging from smartphones and …

Computer vision methods for depth estimation usually use simple camera models with
idealized optics. For modern machine learning approaches, this creates an issue when …

Stereo imaging is the most common passive method for producing reliable depth maps.
Calibration is a crucial step for every stereo-based system, and despite all the …

We present an alternative approach to tomographic particle image velocimetry (tomo-PIV)
that seeks to recover nearly single voxel particles rather than blobs of extended size. The …

Passive and convenient depth estimation from single-shot image is still an open problem.
Existing depth from defocus methods require multiple input images or special hardware …

In this paper we present a single-lens single-frame passive depth sensor based on
conventional imaging system with minor hardware modifications. It is based on color-coded …