While conventional cameras offer versatility for applications ranging from amateur
photography to autonomous driving, computational cameras allow for domain-specific …

Recovering sharp images from dual-pixel (DP) pairs with disparity-dependent blur is a
challenging task. Existing blur map-based deblurring methods have demonstrated …

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 …

The dual-pixel (DP) sensor captures a two-view image pair in a single snapshot by splitting
each pixel in half. The disparity occurs in defocus blurred regions between the two views of …

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

Image deblurring continues to achieve impressive performance with the development of
generative models. Nonetheless, there still remains a displeasing problem if one wants to …

Dual-pixel photography is monocular RGB-D photography with an ultra-high resolution,
enabling many applications in computational photography. However, there are still several …

Reducing the defocus blur that arises from the finite aperture size and short exposure time is
an essential problem in computational photography. It is very challenging because the blur …