DeepAI
Log In Sign Up

FastRIFE: Optimization of Real-Time Intermediate Flow Estimation for Video Frame Interpolation

05/27/2021
by   Malwina Kubas, et al.
0

The problem of video inter-frame interpolation is an essential task in the field of image processing. Correctly increasing the number of frames in the recording while maintaining smooth movement allows to improve the quality of played video sequence, enables more effective compression and creating a slow-motion recording. This paper proposes the FastRIFE algorithm, which is some speed improvement of the RIFE (Real-Time Intermediate Flow Estimation) model. The novel method was examined and compared with other recently published algorithms. All source codes are available at https://gitlab.com/malwinq/interpolation-of-images-for-slow-motion-videos

READ FULL TEXT

page 2

page 3

page 5

page 6

11/12/2020

RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation

We propose RIFE, a Real-time Intermediate Flow Estimation algorithm for ...
12/02/2021

Video Frame Interpolation without Temporal Priors

Video frame interpolation, which aims to synthesize non-exist intermedia...
08/15/2021

Asymmetric Bilateral Motion Estimation for Video Frame Interpolation

We propose a novel video frame interpolation algorithm based on asymmetr...
10/08/2018

Inter-BMV: Interpolation with Block Motion Vectors for Fast Semantic Segmentation on Video

Models optimized for accuracy on single images are often prohibitively s...
03/18/2021

CDFI: Compression-Driven Network Design for Frame Interpolation

DNN-based frame interpolation–that generates the intermediate frames giv...
07/25/2022

Error-Aware Spatial Ensembles for Video Frame Interpolation

Video frame interpolation (VFI) algorithms have improved considerably in...
09/09/2022

Sparsity-guided Network Design for Frame Interpolation

DNN-based frame interpolation, which generates intermediate frames from ...