Depth estimation and shape from focus (SFF) techniques remain at the forefront of computer vision research, addressing the challenge of recovering three-dimensional structural information from ...

In an image, estimating the distance between objects and the camera by using the blur in the images as clue, also known as depth from focus/defocus, is essential in computer vision. However, ...

The first row is the reference image, and the second and third rows are warped images from adjacent images using ground truth depth and pose. Understanding the 3D structure of scenes is an essential ...

Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and ...

Computer vision continues to be one of the most dynamic and impactful fields in artificial intelligence. Thanks to breakthroughs in deep learning, architecture design and data efficiency, machines are ...

Many of today's businesses have recognized the benefits of AI. McKinsey reports that computer vision ranks second among all other AI solutions in terms of application, and Statista research predicts ...

The proposed method takes as input the focal stack and camera settings, and establishes a cost volume based on a lens defocus model. This design enables depth estimation with different camera settings ...