An end-to-end video restoration project with open-source pretrained deep learning models
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Updated
Apr 5, 2020 - Jupyter Notebook
An end-to-end video restoration project with open-source pretrained deep learning models
Upscale any number of videos using this colab notebook!
TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution, CVPR 2020
[CVPR'22 Oral] TTVSR: Learning Trajectory-Aware Transformer for Video Super-Resolution
Pytorch implementation of the model proposed by the IVL team for the AIM 2022 challenge on super-resolution of compressed videos
Recurrent Video Restoration Transformer with Guided Deformable Attention (NeurlPS2022, official repository)
This repository is part of an ongoing personal project to understand and improve video/image restoration and processing.
Method and experience of winning the NTIRE'22 VQE challenge.
[ECCV'22] FTVSR: Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution
Official implementation of "MFQE 2.0: A New Approach for Multi-frame Quality Enhancement on Compressed Video" (TPAMI'19).
Implementation of "Spatio-Temporal Deformable Convolution for Compressed Video Quality Enhancement" (AAAI'20).
VRT: A Video Restoration Transformer (official repository)
Pytorch implementation of the paper "MdVRNet: Deep Video Restoration under Multiple Distortions" (VISAPP 2022)
Image restoration for deep-sea ROV underwater images and videos.
Video restoration based on deep learning: a comprehensive survey
[IEEE TMM 2023] This is the official repo of the paper "Perceptual Quality Improvement in Videoconferencing using Keyframes-based GAN".
[ACM MM 2022 - Demo] Restoration of Analog Videos Using Swin-UNet
Tubitak119e578 project: A novel detection and restoration pipeline for Phase Contrast Microscopy Time Series images
Empower the quality enhancement approaches for compressed videos.
[WACV 2024] - Reference-based Restoration of Digitized Analog Videotapes
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