Efficient Multi-Stage Video Denoising With Recurrent Spatio-Temporal Fusion. CVPR_2021.
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Updated
Jul 21, 2021 - Python
Efficient Multi-Stage Video Denoising With Recurrent Spatio-Temporal Fusion. CVPR_2021.
A Python implementation of a classical video denoising method, VNLB. Numba + Pytorch are used to achieve GPU parallelism.
Extending the LIDIA non-local denoiser to (i) videos and (ii) standard resolutions
Recurrent Video Restoration Transformer with Guided Deformable Attention (NeurlPS2022, official repository)
Run any temporal denoiser on motion-compensated frames, powered by MVTools.
Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Ones (ECCV 2022)
An AI driven Video manipulation toolkit
VRT: A Video Restoration Transformer (official repository)
Python Implementation of Robust PCA
A comparison tool to aid image/video enhancement research
[ NeurIPS 2024 ] The official PyTorch implementation for Learning Truncated Causal History Model for Video Restoration.
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