Progress in the last decade has brought about significant improvements in the accuracy and
speed of SLAM systems, broadening their mapping capabilities. Despite these …

Real-time video deblurring still remains a challenging task due to the complexity of spatially
and temporally varying blur itself and the requirement of low computational cost. To improve …

Video deblurring is a challenging task due to the spatially variant blur caused by camera
shake, object motions, and depth variations, etc. Existing methods usually estimate optical …

Video deblurring is still a challenging low-level vision task since spatio-temporal
characteristics across both the spatial and temporal domains are difficult to model. In this …

Camera shake or target movement often leads to undesired blur effects in videos captured
by a hand-held camera. Despite significant efforts having been devoted to video-deblur …

Recently, video deblurring has attracted considerable research attention, and several works
suggest that events at high time rate can benefit deblurring. In this paper, we develop a …

State-of-the-art video deblurring methods are capable of removing non-uniform blur caused
by unwanted camera shake and/or object motion in dynamic scenes. However, most existing …

The key success factor of the video deblurring methods is to compensate for the blurry pixels
of the mid-frame with the sharp pixels of the adjacent video frames. Therefore, mainstream …

This invited Review discusses causal learning in the context of robotic intelligence. The
Review introduces the psychological findings on causal learning in human cognition, as well …

Video deblurring has achieved remarkable progress thanks to the success of deep neural
networks. Most methods solve for the deblurring end-to-end with limited information …