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.
[ECCV'22] FTVSR: Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution
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
[WACV 2024] - Reference-based Restoration of Digitized Analog Videotapes
[CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur
Video restoration Processing Pipeline
Official repository for the paper titled "Bitstream-corrupted Video Recovery: A Novel Benchmark Dataset and Method", accepted by NeurIPS 2023 Dataset and Benchmark Track
This is a summary of research on All-In-One Image/Video Restoration. There may be omissions. If anything is missing please get in touch with us. Our emails: liboyun.gm@gmail.com; gouyuanbiao@gmail.com; haiyuzhao.gm@gmail.com; wangwenxin.gm@gmail.com
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