An end-to-end video restoration project with open-source pretrained deep learning models
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Updated
Apr 5, 2020 - Jupyter Notebook
Frame interpolation is used to increase the frame rate of a video, or to create a slow-motion video without lowering the frame rate.
An end-to-end video restoration project with open-source pretrained deep learning models
A list of resources for video enhancement, including video super-resolutio, interpolation, denoising, compression artifact removal et al..
Implementation of "Quadratic video interpolation", NeurIPS 2019.
Depth-Aware Video Frame Interpolation (CVPR 2019)
A minimal implementation of TimeLens along with custom data for my final project in Computational Photography 15-463 F21
Video Frame Interpolation Based on Deformable Kernel Region (IJCAI 2022)
CAIN, Channel Attention Is All You Need for Video Frame Interpolation implemented with ncnn library
this app can convert any video frames to 60FPS using ffmpeg motion-interpolation technology.
A Super SloMo TF2 implementation
DAIN, Depth-Aware Video Frame Interpolation implemented with ncnn library
A curated list of resources for Low-level Vision Tasks
GMFlow based video frame interpolation
My own GAN implementation (WGAN-GP with Pytorch)
RIFE, Real-Time Intermediate Flow Estimation for Video Frame Interpolation implemented with ncnn library
Video Frame Interpolation using machine learning. Free and TRUE open source.
Google colab method for high resolution file (4k,...)