Frame Interpolation

Video, Image and GIF upscale/enlarge(Super-Resolution) and Video frame interpolation. Achieved with Waifu2x, Real-ESRGAN, Real-CUGAN, SRMD, RealSR, Anime4K, RIFE, CAIN, DAIN, and ACNet.

PyTorch implementation of Super SloMo by Jiang et al.

FILM: Frame Interpolation for Large Motion, In arXiv 2022.

A Collection of Papers and Codes for CVPR2021/CVPR2020 Low Level Vision

The code for CVPR21 paper "Deep Animation Video Interpolation in the Wild"

Source code for AAAI 2020 paper "Channel Attention Is All You Need for Video Frame Interpolation"

A Collection of Papers and Codes for ICCV2021 Low Level Vision and Image Generation

Official repository of XVFI (ICCV 2021, Oral)

The waifu2x on Mac

Source code for CVPR 2020 paper "Scene-Adaptive Video Frame Interpolation via Meta-Learning"

Official PyTorch implementation of "Deep Slow Motion Video Reconstruction with Hybrid Imaging System" (TPAMI)

Official repository of FISR (AAAI 2020).

Tensorflow 2 implementation of Super SloMo paper

An end-to-end video restoration project with open-source pretrained deep learning models

Frame interpolation

Official MegEngine implementation of RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation,

CoreML+Metal implementation of "Video Frame Interpolation via Adaptive Separable Convolution"

PyTorch Implementation of "Robust Temporal Super-Resolution for Dynamic Motion Video", ICCVW, AIM2019

Middlebury's frame interpolation method

Video frame interpolation using the Vimeo-90k dataset.

In this repository, we deal with the task of video frame interpolation with estimated optical flow. To estimate the optical flow we use Lucas-Kanade algorithm, Multiscale Lucas-Kanade algorithm (with iterative tuning), and Discrete Horn-Schunk algorithm. We explore the interpolation performance on Spheres dataset and Corridor dataset.

In this repository, we deal with the task of video frame interpolation with estimated optical flow. To estimate the optical flow we use pre-trained FlowNet2 deep learning model and experiment by fine-tuning it. We explore the interpolation performance on Spheres dataset and Corridor dataset.

Enhance the quality of your videos

Predictive Frame Interpolation (PIF) Model for video frame prediction and generation. The model can generate in between frames of a video thus increasing the frame rate.

Implementation of the paper "Video Frame Interpolation by Plug-and-Play Deep Locally Temporal Embedding"

Motion Compensated Frame Interpolation using Deep ConvNets

Estimating frame[t] given frames frame[t-1] and frame[t+1]

A fork of the SuperSloMo repository, modified in various ways to experiment with the capabilitiets of the nural net.

SVPlite - Realtime-Optimized AviSynth+ Script-Templates for the SmoothVideo Project's SVPflow filters. Portable Low-Resource Motion Interpolation.

FILM: Frame Interpolation for Large Motion