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

OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc.

VRT: A Video Restoration Transformer (official repository)

[ICML 2024] EvTexture: Event-driven Texture Enhancement for Video Super-Resolution

[CVPR 2024] Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolution

Fast and Accurate One-Stage Space-Time Video Super-Resolution (accepted in CVPR 2020)

A list of resources for video enhancement, including video super-resolutio, interpolation, denoising, compression artifact removal et al..

Official codes of VEnhancer: Generative Space-Time Enhancement for Video Generation

Recurrent Video Restoration Transformer with Guided Deformable Attention (NeurlPS2022, official repository)

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

[CVPR 2022] Official PyTorch Implementation for "Reference-based Video Super-Resolution Using Multi-Camera Video Triplets"

[CVPR'22 Oral] TTVSR: Learning Trajectory-Aware Transformer for Video Super-Resolution

Video super resolution implemented in Pytorch

Frame-Recurrent Video Super-Resolution (official repository)

a collection of classic tensorflow & pytorch cnn models' implementation

[ECCV'22] FTVSR: Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution

Super-resolution videos in macOS with Waifu2x.

[ECCV 2024] Enhancing Perceptual Quality in Video Super-Resolution through Temporally-Consistent Detail Synthesis using Diffusion Models

Latest development of ISR/VSR. Papers and related resources, mainly state-of-the-art and novel works in ICCV, ECCV and CVPR about image super-resolution and video super-resolution.

It is a re-implementation of paper named "Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation" called VSR-DUF model. There are both training codes and test codes about VSR-DUF based tensorflow.