SOTAVerified

Video Super-Resolution

Video Super-Resolution is a computer vision task that aims to increase the resolution of a video sequence, typically from lower to higher resolutions. The goal is to generate high-resolution video frames from low-resolution input, improving the overall quality of the video.

( Image credit: Detail-revealing Deep Video Super-Resolution )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 281 papers

TitleStatusHype
Improving Generative Adversarial Networks for Video Super-Resolution—0
Information Prebuilt Recurrent Reconstruction Network for Video Super-Resolution—0
In-situ monitoring additive manufacturing process with AI edge computing—0
Efficient and Phase-aware Video Super-resolution for Cardiac MRI—0
Efficient Video Super-Resolution for Real-time Rendering with Decoupled G-buffer Guidance—0
Turning Frequency to Resolution: Video Super-Resolution via Event Cameras—0
End-to-End Learning of Video Super-Resolution with Motion Compensation—0
End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation—0
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space—0
Understanding Deformable Alignment in Video Super-Resolution—0
A Novel Dual Dense Connection Network for Video Super-resolution—0
Self-Enhanced Convolutional Network for Facial Video Hallucination—0
Event-based Video Super-Resolution via State Space Models—0
A New Adaptive Video Super-Resolution Algorithm With Improved Robustness to Innovations—0
EVRNet: Efficient Video Restoration on Edge Devices—0
An End-Cloud Computing Enabled Surveillance Video Transmission System—0
Expanding Synthetic Real-World Degradations for Blind Video Super Resolution—0
GRNN:Recurrent Neural Network based on Ghost Features for Video Super-Resolution—0
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
Fast Spatio-Temporal Residual Network for Video Super-Resolution—0
FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution—0
Feature Aggregating Network with Inter-Frame Interaction for Efficient Video Super-Resolution—0
Self-supervised ControlNet with Spatio-Temporal Mamba for Real-world Video Super-resolution—0
FMA-Net: Flow-Guided Dynamic Filtering and Iterative Feature Refinement with Multi-Attention for Joint Video Super-Resolution and Deblurring—0
Frame and Feature-Context Video Super-Resolution—0
Show:102550
← PrevPage 6 of 12Next →
All datasetsMSU Super-Resolution for Video CompressionMSU Video Upscalers: Quality EnhancementMSU Video Super Resolution Benchmark: Detail RestorationVid4 - 4x upscalingVid4 - 4x upscaling - BD degradationREDS4- 4x upscalingUDM10 - 4x upscalingUltra Video Group HD - 4x upscalingFalling ObjectsTbDTbD-3DVimeo90K

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1bicubic + uavs3eBSQ-rate over ERQA21.97—Unverified
2bicubic + aomencBSQ-rate over ERQA21.97—Unverified
3RealSR + vvencBSQ-rate over ERQA21.97—Unverified
4bicubic + vvencBSQ-rate over ERQA21.97—Unverified
5TMNet + aomencBSQ-rate over ERQA21.8—Unverified
6TMNet + vvencBSQ-rate over ERQA21.3—Unverified
7RSDN + aomencBSQ-rate over ERQA20.62—Unverified
8RSDN + uavs3eBSQ-rate over ERQA18.33—Unverified
9EGVSR + aomencBSQ-rate over ERQA16.73—Unverified
10bicubic + x265BSQ-rate over ERQA16.01—Unverified
#ModelMetricClaimedVerifiedStatus
1LGFNSSIM0.94—Unverified
2iSeeBetterSSIM0.94—Unverified
3DBVSRSSIM0.94—Unverified
4SOF-VSRSSIM0.94—Unverified
5FRVSRSSIM0.94—Unverified
6ESRGANSSIM0.94—Unverified
7SPMCSSIM0.93—Unverified
8TecoGANSSIM0.93—Unverified
9DRRNSSIM0.93—Unverified
10VESPCNSSIM0.93—Unverified
#ModelMetricClaimedVerifiedStatus
1VRTSubjective score7.63—Unverified
2BasicVSRSubjective score7.19—Unverified
3RBPNSubjective score7.07—Unverified
4DBVSRSubjective score6.95—Unverified
5iSeeBetterSubjective score6.81—Unverified
6LGFNSubjective score6.51—Unverified
7DynaVSR-RSubjective score6.14—Unverified
8TMNetSubjective score6—Unverified
9COMISRSubjective score5.64—Unverified
10RSDNSubjective score5.57—Unverified
#ModelMetricClaimedVerifiedStatus
1VideoGigaGANPSNR27.04—Unverified
2TecoGAN⊖PSNR25.89—Unverified
3TecoGANPSNR25.57—Unverified
4EvTexture+SSIM0.9—Unverified
5EvTextureSSIM0.89—Unverified
6IARTSSIM0.85—Unverified
7MIA-VSRSSIM0.85—Unverified
8CFD-PSRTSSIM0.85—Unverified
9PSRT-recurrentSSIM0.85—Unverified
10RVRTSSIM0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1RVRTPSNR29.54—Unverified
2VRTPSNR29.42—Unverified
3BasicVSR++PSNR29.04—Unverified
4FTVSRPSNR28.7—Unverified
5GOVSRPSNR28.41—Unverified
6TTVSRPSNR28.4—Unverified
7IconVSRPSNR28.04—Unverified
8BasicVSRPSNR27.96—Unverified