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 1–10 of 281 papers

TitleStatusHype
Compressed Video Super-Resolution based on Hierarchical Encoding—0
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 4090s—0
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 Compensation—0
Omnidirectional Video Super-Resolution using Deep Learning—0
A Survey of Deep Learning Video Super-Resolution—0
UltraVSR: Achieving Ultra-Realistic Video Super-Resolution with Efficient One-Step Diffusion Space—0
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-ResolutionCode2
Show:102550
← PrevPage 1 of 29Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RealSR + vvencBSQ-rate over ERQA21.97—Unverified
2bicubic + aomencBSQ-rate over ERQA21.97—Unverified
3bicubic + uavs3eBSQ-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