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SOTA
Video Denoising
Video Denoising On Davis Sigma30
Video Denoising On Davis Sigma30
Metrics
PSNR
Results
Performance results of various models on this benchmark
Columns
Model Name
PSNR
Paper Title
ReViD
36.97
Learning Task-Oriented Flows to Mutually Guide Feature Alignment in Synthesized and Real Video Denoising
RVRT
36.57
Recurrent Video Restoration Transformer with Guided Deformable Attention
VRT
36.52
VRT: A Video Restoration Transformer
PaCNet
34.79
Patch Craft: Video Denoising by Deep Modeling and Patch Matching
DVDnet
34.08
DVDnet: A Fast Network for Deep Video Denoising
FastDVDnet
34.06
FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation
UDVD
33.92
Unsupervised Deep Video Denoising
0 of 7 row(s) selected.
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HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Video Denoising
Video Denoising On Davis Sigma30
Video Denoising On Davis Sigma30
Metrics
PSNR
Results
Performance results of various models on this benchmark
Columns
Model Name
PSNR
Paper Title
ReViD
36.97
Learning Task-Oriented Flows to Mutually Guide Feature Alignment in Synthesized and Real Video Denoising
RVRT
36.57
Recurrent Video Restoration Transformer with Guided Deformable Attention
VRT
36.52
VRT: A Video Restoration Transformer
PaCNet
34.79
Patch Craft: Video Denoising by Deep Modeling and Patch Matching
DVDnet
34.08
DVDnet: A Fast Network for Deep Video Denoising
FastDVDnet
34.06
FastDVDnet: Towards Real-Time Deep Video Denoising Without Flow Estimation
UDVD
33.92
Unsupervised Deep Video Denoising
0 of 7 row(s) selected.
Previous
Next
Video Denoising On Davis Sigma30 | SOTA | HyperAI