Video super-resolution (VSR) is reconstructing high-resolution videos from low resolution
ones. Recently, the VSR methods based on deep neural networks have made great …

Generative Adversarial Networks (GANs) have shown remarkable success in producing
realistic-looking images in the computer vision area. Recently, GAN-based techniques are …

We observe that despite their hierarchical convolutional nature, the synthesis process of
typical generative adversarial networks depends on absolute pixel coordinates in an …

Video restoration aims at restoring multiple high-quality frames from multiple low-quality
frames. Existing video restoration methods generally fall into two extreme cases, ie, they …

Recent implicit neural rendering methods have demonstrated that it is possible to learn
accurate view synthesis for complex scenes by predicting their volumetric density and color …

In this paper, we firstly present a dataset (X4K1000FPS) of 4K videos of 1000 fps with the
extreme motion to the research community for video frame interpolation (VFI), and propose …

In this paper, we present an extensive review on deep learning methods for image
restoration tasks. Deep learning techniques, led by convolutional neural networks, have …

Generating high-fidelity human video with specified identities has attracted significant
attention in the content generation community. However, existing techniques struggle to …

Compressed video super-resolution (VSR) aims to restore high-resolution frames from
compressed low-resolution counterparts. Most recent VSR approaches often enhance an …

Given its wide applications, there is increasing focus on generating 3D human motions from
textual descriptions. Differing from the majority of previous works, which regard actions as …