Video Frame Interpolation

97 papers with code • 21 benchmarks • 12 datasets

The goal of Video Frame Interpolation is to synthesize several frames in the middle of two adjacent frames of the original video. Video Frame Interpolation can be applied to generate slow motion video, increase video frame rate, and frame recovery in video streaming.

Source: Reducing the X-ray radiation exposure frequency in cardio-angiography via deep-learning based video interpolation


Use these libraries to find Video Frame Interpolation models and implementations

Most implemented papers

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

hzwer/Arxiv2020-RIFE 12 Nov 2020

We propose RIFE, a Real-time Intermediate Flow Estimation algorithm for Video Frame Interpolation (VFI).

Video Frame Interpolation via Adaptive Separable Convolution

sniklaus/sepconv-slomo ICCV 2017

Our method develops a deep fully convolutional neural network that takes two input frames and estimates pairs of 1D kernels for all pixels simultaneously.

Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation

avinashpaliwal/Super-SloMo CVPR 2018

Finally, the two input images are warped and linearly fused to form each intermediate frame.

Depth-Aware Video Frame Interpolation

baowenbo/DAIN CVPR 2019

The proposed model then warps the input frames, depth maps, and contextual features based on the optical flow and local interpolation kernels for synthesizing the output frame.

Video Enhancement with Task-Oriented Flow

anchen1011/toflow 24 Nov 2017

Many video enhancement algorithms rely on optical flow to register frames in a video sequence.

Implementing Adaptive Separable Convolution for Video Frame Interpolation

martkartasev/sepconv 20 Sep 2018

As Deep Neural Networks are becoming more popular, much of the attention is being devoted to Computer Vision problems that used to be solved with more traditional approaches.

Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution

Mukosame/Zooming-Slow-Mo-CVPR-2020 CVPR 2020

Rather than synthesizing missing LR video frames as VFI networks do, we firstly temporally interpolate LR frame features in missing LR video frames capturing local temporal contexts by the proposed feature temporal interpolation network.

ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation

danielism97/st-mfnet CVPR 2022

Video frame interpolation (VFI) is currently a very active research topic, with applications spanning computer vision, post production and video encoding.

Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time

shangwei5/vidue CVPR 2023

Moreover, on the seemingly implausible x16 interpolation task, our method outperforms existing methods by more than 1. 5 dB in terms of PSNR.