SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–75 of 3874 papers

TitleStatusHype
PP-MSVSR: Multi-Stage Video Super-ResolutionCode3
SwinIR: Image Restoration Using Swin TransformerCode3
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and AlignmentCode3
BasicVSR: The Search for Essential Components in Video Super-Resolution and BeyondCode3
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative ModelsCode3
ESRGAN: Enhanced Super-Resolution Generative Adversarial NetworksCode3
Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature TransformCode3
EAMamba: Efficient All-Around Vision State Space Model for Image RestorationCode2
DOVE: Efficient One-Step Diffusion Model for Real-World Video Super-ResolutionCode2
VisualQuality-R1: Reasoning-Induced Image Quality Assessment via Reinforcement Learning to RankCode2
NTIRE 2025 Challenge on Image Super-Resolution (4): Methods and ResultsCode2
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-ResolutionCode2
ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion RefinementCode2
Progressive Focused Transformer for Single Image Super-ResolutionCode2
Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality AssumptionCode2
Perceive, Understand and Restore: Real-World Image Super-Resolution with Autoregressive Multimodal Generative ModelsCode2
Emulating Self-attention with Convolution for Efficient Image Super-ResolutionCode2
AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual LearningCode2
DifIISR: A Diffusion Model with Gradient Guidance for Infrared Image Super-ResolutionCode2
Geodesic Diffusion Models for Medical Image-to-Image GenerationCode2
Visual Autoregressive Modeling for Image Super-ResolutionCode2
Efficient Attention-Sharing Information Distillation Transformer for Lightweight Single Image Super-ResolutionCode2
Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-ResolutionCode2
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
MaIR: A Locality- and Continuity-Preserving Mamba for Image RestorationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified