Existing implicit neural representation (INR) methods do not fully exploit spatiotemporal
redundancies in videos. Index-based INRs ignore the content-specific spatial features and …

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

Recently, there has been exciting progress in frame interpolation for rendered content. In
this offline rendering setting, additional inputs, such as albedo and depth, can be extracted …

Currently, the general domain of video reconstruction (VR) is fragmented into different
shutters spanning global shutter and rolling shutter cameras. Despite rapid progress in the …

Implicit neural representations (INR) have been recently proposed as deep learning (DL)
based solutions for image compression. An image can be compressed by training an INR …

This paper introduces a LArge-scale Video Interpolation Benchmark (LAVIB) for the low-
level video task of video frame interpolation (VFI). LAVIB comprises a large collection of high …

The demand for compact cameras capable of recording high-speed scenes with high
resolution is steadily increasing. However, achieving such capabilities often entails high …

The subjective image quality of the Video Frame Interpolation (VFI) result depends on
whether image features such as edges, textures and blobs are preserved. With the …