SOTAVerified

Video Restoration

Papers

Showing 51–75 of 99 papers

TitleStatusHype
DiffMVR: Diffusion-based Automated Multi-Guidance Video Restoration—0
Adapting MIMO video restoration networks to low latency constraints—0
Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration—0
DeTurb: Atmospheric Turbulence Mitigation with Deformable 3D Convolutions and 3D Swin Transformers—0
MNeRV: A Multilayer Neural Representation for VideosCode0
Zero-Shot Video Restoration and Enhancement Using Pre-Trained Image Diffusion ModelCode0
DaBiT: Depth and Blur informed Transformer for Joint Refocusing and Super-ResolutionCode0
HR-INR: Continuous Space-Time Video Super-Resolution via Event CameraCode0
SC-HVPPNet: Spatial and Channel Hybrid-Attention Video Post-Processing Network with CNN and Transformer—0
Turb-Seg-Res: A Segment-then-Restore Pipeline for Dynamic Videos with Atmospheric Turbulence—0
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention BlocksCode0
VJT: A Video Transformer on Joint Tasks of Deblurring, Low-light Enhancement and Denoising—0
MR-VNet: Media Restoration using Volterra Networks—0
ViStripformer: A Token-Efficient Transformer for Versatile Video RestorationCode0
ConVRT: Consistent Video Restoration Through Turbulence with Test-time Optimization of Neural Video Representations—0
FLAIR: A Conditional Diffusion Framework with Applications to Face Video RestorationCode0
A New Real-World Video Dataset for the Comparison of Defogging Algorithms—0
Deep Video Restoration for Under-Display Camera—0
Cross-Consistent Deep Unfolding Network for Adaptive All-In-One Video Restoration—0
Dual Inverse Degradation Network for Real-World SDRTV-to-HDRTV Conversion—0
Neural Image Re-ExposureCode0
Unlocking Masked Autoencoders as Loss Function for Image and Video Restoration—0
ReBotNet: Fast Real-time Video Enhancement—0
Learning Physical-Spatio-Temporal Features for Video Shadow Removal—0
Leveraging Video Coding Knowledge for Deep Video Enhancement—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DiQP on AV1 with QP 255Average PSNR (dB)34.87—Unverified
2DiQP on HVEC with QP 51Average PSNR (dB)34.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DiQP on AV1 with QP 255Average PSNR (dB)32.55—Unverified
2DiQP on HVEC with QP 51Average PSNR (dB)31.97—Unverified