As one of the fundamental technologies for scene understanding, semantic segmentation
has been widely explored in the last few years. Light field cameras encode the geometric …

Different from the object motion blur, the defocus blur is caused by the limitation of the
cameras' depth of field. The defocus amount can be characterized by the parameter of point …

Light Field (LF) imaging is a promising solution for providing more immersive and closer to
reality multimedia experiences to end-users with unprecedented creative freedom and …

Defocus blur often degrades the performance of image understanding, such as object
recognition and image segmentation. Restoring an all-in-focus image from its defocused …

4D light fields capture both the intensity and direction of light, enabling appealing effects
such as viewpoint change, synthetic aperture, and refocusing. However, capturing a light …

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) …

Traditional focal stack methods require multiple shots to capture images focused at different
distances of the same scene, which cannot be applied to dynamic scenes well. Generating a …

Creating an image focal stack requires multiple shots, which captures images at different
depths within the same scene. Such methods are not suitable for scenes undergoing …

Light field data exhibit favorable characteristics conducive to saliency detection. The
success of learning-based light field saliency detection is heavily dependent on how a …

Multi-focus image fusion, a technique to generate an all-in-focus image from two or more
partially-focused source images, can benefit many computer vision tasks. However, currently …