ant-research/CoDeF
A PyTorch implementation of CoDeF, a neural video representation using canonical content and temporal deformation fields to lift image algorithms to video processing.

CoDeF proposes a video representation consisting of a canonical content field that aggregates static content across a video and a temporal deformation field that records transformations from the canonical image to each frame. These two fields are jointly optimized to reconstruct the target video through a tailored rendering pipeline. The approach enables lifting image-processing algorithms to video by applying them to the canonical image and propagating results via the deformation field.