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

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Showing 151–200 of 281 papers

TitleStatusHype
Optical Flow for Video Super-Resolution: A Survey—0
STDAN: Deformable Attention Network for Space-Time Video Super-ResolutionCode1
A Novel Dual Dense Connection Network for Video Super-resolution—0
Spatio-temporal Vision Transformer for Super-resolution MicroscopyCode1
Fast Online Video Super-Resolution with Deformable Attention Pyramid—0
VRT: A Video Restoration TransformerCode3
Deep Networks for Image and Video Super-Resolution—0
Self-Supervised Deep Blind Video Super-ResolutionCode1
Stable Long-Term Recurrent Video Super-ResolutionCode1
Information Prebuilt Recurrent Reconstruction Network for Video Super-Resolution—0
PP-MSVSR: Multi-Stage Video Super-ResolutionCode3
Revisiting Temporal Alignment for Video RestorationCode1
Investigating Tradeoffs in Real-World Video Super-ResolutionCode2
AdaPool: Exponential Adaptive Pooling for Information-Retaining DownsamplingCode1
MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution—0
ERQA: Edge-Restoration Quality Assessment for Video Super-ResolutionCode1
EFENet: Reference-based Video Super-Resolution with Enhanced Flow EstimationCode1
Optical Flow Reusing for High-Efficiency Space-Time Video Super Resolution—0
An Efficient Network Design for Face Video Super-resolutionCode0
Memory-Augmented Non-Local Attention for Video Super-ResolutionCode1
SwinIR: Image Restoration Using Swin TransformerCode3
Temporal Kernel Consistency for Blind Video Super-Resolution—0
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image RescalingCode1
Ada-VSR: Adaptive Video Super-Resolution with Meta-Learning—0
Self-Conditioned Probabilistic Learning of Video RescalingCode1
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic DataCode4
Real-Time Super-Resolution System of 4K-Video Based on Deep LearningCode1
Video Super-Resolution with Long-Term Self-Exemplars—0
Applying VertexShuffle Toward 360-Degree Video Super-Resolution on Focused-Icosahedral-Mesh—0
Space-Time Distillation for Video Super-Resolution—0
Turning Frequency to Resolution: Video Super-Resolution via Event Cameras—0
Group-based Bi-Directional Recurrent Wavelet Neural Networks for Video Super-Resolution—0
Video Super-Resolution TransformerCode1
Real-Time Video Super-Resolution on Smartphones with Deep Learning, Mobile AI 2021 Challenge: Report—0
FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution—0
Real-Time Video Super-Resolution by Joint Local Inference and Global Parameter Estimation—0
COMISR: Compression-Informed Video Super-ResolutionCode0
NTIRE 2021 Challenge on Video Super-Resolution—0
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and AlignmentCode3
Temporal Modulation Network for Controllable Space-Time Video Super-ResolutionCode1
Zooming SlowMo: An Efficient One-Stage Framework for Space-Time Video Super-ResolutionCode1
Omniscient Video Super-Resolution—0
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling—0
Self-Supervised Adaptation for Video Super-ResolutionCode1
Learning for Unconstrained Space-Time Video Super-Resolution—0
Deep Unrolled Network for Video Super-Resolution—0
Towards Real-World Blind Face Restoration with Generative Facial PriorCode4
Dual-Stream Fusion Network for Spatiotemporal Video Super-ResolutionCode0
Real-World Video Super-Resolution: A Benchmark Dataset and a Decomposition Based Learning SchemeCode1
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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
1iSeeBetterSSIM0.94—Unverified
2LGFNSSIM0.94—Unverified
3SOF-VSRSSIM0.94—Unverified
4DBVSRSSIM0.94—Unverified
5FRVSRSSIM0.94—Unverified
6ESRGANSSIM0.94—Unverified
7DRRNSSIM0.93—Unverified
8TecoGANSSIM0.93—Unverified
9SPMCSSIM0.93—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