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

Showing 110 of 281 papers

TitleStatusHype
Compressed Video Super-Resolution based on Hierarchical Encoding0
FCA2: Frame Compression-Aware Autoencoder for Modular and Fast Compressed Video Super-ResolutionCode0
ICME 2025 Grand Challenge on Video Super-Resolution for Video ConferencingCode1
LiftVSR: Lifting Image Diffusion to Video Super-Resolution via Hybrid Temporal Modeling with Only 4RTX 4090s0
A Systematic Investigation on Deep Learning-Based Omnidirectional Image and Video Super-ResolutionCode0
DualX-VSR: Dual Axial SpatialTemporal Transformer for Real-World Video Super-Resolution without Motion Compensation0
Omnidirectional Video Super-Resolution using Deep Learning0
A Survey of Deep Learning Video Super-Resolution0
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space0
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-ResolutionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1LGFNSSIM0.94Unverified
2iSeeBetterSSIM0.94Unverified
3SOF-VSRSSIM0.94Unverified
4DBVSRSSIM0.94Unverified
5ESRGANSSIM0.94Unverified
6FRVSRSSIM0.94Unverified
7TecoGANSSIM0.93Unverified
8SPMCSSIM0.93Unverified
9DRRNSSIM0.93Unverified
10VESPCNSSIM0.93Unverified