Video Super-Resolution

End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation

Video super-resolution aims at generating a high-resolution video from its low-resolution counterpart. With the rapid rise of deep learning, many recently proposed video super-resolution methods use convolutional neural networks in conjunction with …

Video Super-Resolution via Dynamic Local Filter Network

Conventional Convolutional Neural Network (CNN) based video super-resolution (VSR) methods heavily depend on explicit motion compensation. Input frames are warped according to flow-like information to eliminate inter-frame differences. These methods …