SOTAVerified

Video Restoration

Papers

Showing 26–50 of 99 papers

TitleStatusHype
Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video DeblurringCode1
Making Old Film Great Again: Degradation-aware State Space Model for Old Film RestorationCode1
Toward Accurate and Temporally Consistent Video Restoration from Raw DataCode1
SwinTExCo: Exemplar-based video colorization using Swin TransformerCode1
VDTR: Video Deblurring with TransformerCode1
DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive BoostingCode1
Physical prior guided cooperative learning framework for joint turbulence degradation estimation and infrared video restoration—0
Proposal-based Video Completion—0
ReBotNet: Fast Real-time Video Enhancement—0
Removing Multiple Hybrid Adverse Weather in Video via a Unified Model—0
Restoration of Video Frames from a Single Blurred Image with Motion Understanding—0
Restore from Restored: Video Restoration with Pseudo Clean Video—0
UniFlowRestore: A General Video Restoration Framework via Flow Matching and Prompt Guidance—0
Adapting MIMO video restoration networks to low latency constraints—0
A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment—0
A New Real-World Video Dataset for the Comparison of Defogging Algorithms—0
CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices—0
ConVRT: Consistent Video Restoration Through Turbulence with Test-time Optimization of Neural Video Representations—0
Cross-Consistent Deep Unfolding Network for Adaptive All-In-One Video Restoration—0
Deep Multi-modality Soft-decoding of Very Low Bit-rate Face Videos—0
Deep Video Restoration for Under-Display Camera—0
DeTurb: Atmospheric Turbulence Mitigation with Deformable 3D Convolutions and 3D Swin Transformers—0
DiffMVR: Diffusion-based Automated Multi-Guidance Video Restoration—0
Dynamic Content Prediction with Motion-aware Priors for Blind Face Video Restoration—0
Editorial: Introduction to the Issue on Deep Learning for Image/Video Restoration and Compression—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