We present a method that takes as input a single dual-pixel image, and simultaneously
estimates the image's defocus map---the amount of defocus blur at each pixel---and …

Depth estimation is a long-lasting yet important task in computer vision. Most of the previous
works try to estimate depth from input images and assume images are all-in-focus (AiF) …

Artificial intelligence systems are becoming increasingly available as diagnostic aids for
optometric practice. These perform well but are often 'black-box'systems offering little or no …

Autofocusing system plays an important role in microscopic measurement. However, natural-
image-based autofocus methods encounter difficulties in improving focusing accuracy and …

The dual-pixel (DP) hardware works by splitting each pixel in half and creating an image
pair in a single snapshot. Several works estimate depth/inverse depth by treating the DP pair …

Most digital cameras use specialized autofocus sensors, such as phase detection, lidar or
ultrasound, to directly measure focus state. However, such sensors increase cost and …

For better photography, most recent commercial cameras including smartphones have either
adopted large-aperture lens to collect more light or used a burst mode to take multiple …

By adopting popular pixel-wise loss, existing methods for defocus deblurring heavily rely on
well aligned training image pairs. Although training pairs of ground-truth and blurry images …

In digital photography, autofocus is a key feature that aids high-quality image capture, and
modern approaches use the phase patterns arising from dual-pixel sensors as important …

Smartphone cameras today are increasingly approaching the versatility and quality of
professional cameras through a combination of hardware and software advancements …