Description
IFNet is an architecture for video frame interpolation that adopts a coarse-to-fine strategy with progressively increased resolutions: it iteratively updates intermediate flows and soft fusion mask via successive IFBlocks. Conceptually, according to the iteratively updated flow fields, we can move corresponding pixels from two input frames to the same location in a latent intermediate frame and use a fusion mask to combine pixels from two input frames. Unlike most previous optical flow models, IFBlocks do not contain expensive operators like cost volume or forward warping and use 3 × 3 convolution and deconvolution as building blocks.
Papers Using This Method
l0-Regularized Sparse Coding-based Interpretable Network for Multi-Modal Image Fusion2024-11-07IFNet: Deep Imaging and Focusing for Handheld SAR with Millimeter-wave Signals2024-05-03Iterative Feedback Network for Unsupervised Point Cloud Registration2024-01-09Point cloud completion via structured feature maps using a feedback network2022-02-17FastRIFE: Optimization of Real-Time Intermediate Flow Estimation for Video Frame Interpolation2021-05-27RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation2020-11-12