Video stabilization is one of the most fundamental and challenging tasks in video
processing, which can be widely applied in many areas, such as video surveillance …

Image/video stitching is a technology for solving the field of view (FOV) limitation of
images/videos. It stitches multiple overlap** images/videos to generate a wide-FOV …

High-quality video inpainting that completes missing regions in video frames is a promising
yet challenging task. State-of-the-art approaches adopt attention models to complete a frame …

Motion blur from camera shake is a major problem in videos captured by hand-held devices.
Unlike single-image deblurring, video-based approaches can take advantage of the …

We propose a flow-guided transformer, which innovatively leverage the motion discrepancy
exposed by optical flows to instruct the attention retrieval in transformer for high fidelity video …

Video inpainting aims to fill spatio-temporal holes with plausible content in a video. Despite
tremendous progress of deep neural networks for image inpainting, it is challenging to …

How to effectively explore spatial and temporal information is important for video deblurring.
In contrast to existing methods that directly align adjacent frames without discrimination, we …

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 …

We present a simple and effective deep convolutional neural network (CNN) model for video
deblurring. The proposed algorithm mainly consists of optical flow estimation from …

Humans perceive the three-dimensional structure of the world with apparent ease. However,
despite all of the recent advances in computer vision research, the dream of having a …