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

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Showing 401–425 of 3874 papers

TitleStatusHype
Deep Face Super-Resolution with Iterative Collaboration between Attentive Recovery and Landmark EstimationCode1
LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion ModelCode1
A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-ResolutionCode1
Computing Multiple Image Reconstructions with a Single HypernetworkCode1
AutoGAN-Distiller: Searching to Compress Generative Adversarial NetworksCode1
Compression-Aware Video Super-ResolutionCode1
Deep Image PriorCode1
Automatic quality control in multi-centric fetal brain MRI super-resolution reconstructionCode1
Deep Interleaved Network for Image Super-Resolution With Asymmetric Co-AttentionCode1
A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-ResolutionCode1
Conditional Hyper-Network for Blind Super-Resolution with Multiple DegradationsCode1
Deep Learning-Based CKM Construction with Image Super-ResolutionCode1
Efficient and Degradation-Adaptive Network for Real-World Image Super-ResolutionCode1
Fast and Memory-Efficient Network Towards Efficient Image Super-ResolutionCode1
Azimuth Super-Resolution for FMCW Radar in Autonomous DrivingCode1
Adaptive Cross-Layer Attention for Image RestorationCode1
Efficient Conditional Diffusion Model with Probability Flow Sampling for Image Super-resolutionCode1
A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuningCode1
Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-ResolutionCode1
Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-ResolutionCode1
BAM: A Balanced Attention Mechanism for Single Image Super ResolutionCode1
Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity EstimationCode1
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-ResolutionCode1
Crack Segmentation for Low-Resolution Images using Joint Learning with Super-ResolutionCode1
A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net DiscriminatorsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified