[ NeurIPS 2024 ] The official PyTorch implementation for Learning Truncated Causal History Model for Video Restoration.
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Updated
Nov 14, 2024 - Python
[ NeurIPS 2024 ] The official PyTorch implementation for Learning Truncated Causal History Model for Video Restoration.
This repository contains the poster (and its TeX code) for our paper "Learning Truncated Causal History Model for Video Restoration" in NeurIPS 2024.
Rankings include: ABME AdaFNIO ALANET AMT BiT BVFI CDFI CtxSyn DBVI DeMFI DQBC DRVI EAFI EBME EDC EDENVFI EDSC EMA-VFI FGDCN FILM FLAVR HiFI H-VFI IFRNet IQ-VFI JNMR LADDER M2M MA-GCSPA NCM PerVFI PRF ProBoost-Net RIFE RN-VFI SoftSplat SSR ST-MFNet Swin-VFI TDPNet TTVFI UGFI UPR-Net UTI-VFI VFIformer VFIFT VFIMamba VFIT VIDUE VRT
A curated list of research papers and datasets related to image and video deblurring.
Video Deblurring with Transformer
Implementation of "Blur-aware Spatio-temporal Sparse Transformer for Video Deblurring". (Zhang et al., CVPR 2024)
A curated list of resources for Image and Video Deblurring
[TOG 2021] Official PyTorch Implementation for "Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes"
[CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur
Simple framework for image and video deblurring, implemented by PyTorch
[AIR 2023] Video restoration based on deep learning: a comprehensive survey
[ECCV2020 Spotlight] Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring
VRT: A Video Restoration Transformer (official repository)
An AI driven Video manipulation toolkit
[ECCV 2022] Official repository of DeMFI.
Recurrent Video Restoration Transformer with Guided Deformable Attention (NeurlPS2022, official repository)
A list of resources for video enhancement, including video super-resolutio, interpolation, denoising, compression artifact removal et al..
Implementation of “Video Deblurring by Fitting to Test Data“: https://arxiv.org/abs/2012.05228
[ICCV 2019] Spatio-Temporal Filter Adaptive Network for Video Deblurring
Deep Video Deblurring Using Sharpness Features from Exemplars (TIP, 2020) (PyTorch)
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