Motion segmentation is an essential task in artificial intelligence and computer vision.
However, scene motion in real-world intelligent systems usually integrates multiple types of …

Most cameras on portable devices adopt a rolling shutter (RS) mechanism, encoding
sufficient temporal dynamic information through sequential readouts. This advantage can be …

High-resolution high-frame-rate videos can record motion scenes detailedly and smoothly,
but usually only professional cameras have enough transmission bandwidth to meet the …

In this paper, we consider the task of space-time video super-resolution (ST-VSR), which
can increase the spatial resolution and frame rate for a given video simultaneously. Despite …

Video frame interpolation (VFI) is of great importance for many video applications, yet it is
still challenging even in the era of deep learning. Some existing VFI models directly exploit …

Video frame interpolation (VFI) aims to generate predictive frames by motion-war** from
bidirectional references. Most examples of VFI utilize spatiotemporal semantic information to …

Joint space-time video super-resolution aims to increase both the spatial resolution and the
frame rate of a video sequence. As a result, details become more apparent, leading to a …

Video snapshot compressive imaging (SCI) samples 3D high-speed video frames with
temporally varying spatial modulation and compresses them into a single 2D measurement …

Future frame prediction for anomaly detection methods based on memory networks have
been extensively explored in the academic domain. Nevertheless, traditional memory …

By converting low-frame-rate, low-resolution videos into high-frame-rate, high-resolution
ones, space-time video super-resolution techniques can enhance visual experiences and …