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 2251–2300 of 3874 papers

TitleStatusHype
XCycles Backprojection Acoustic Super-Resolution—0
Transformer based super-resolution downscaling for regional reanalysis: Full domain vs tiling approaches—0
Memory-augmented Deep Unfolding Network for Guided Image Super-resolution—0
CoReGAN: Contrastive Regularized Generative Adversarial Network for Guided Depth Map Super Resolution—0
Convolutional Sparse Coding for Image Super-Resolution—0
Memory-efficient Learning for Large-scale Computational Imaging -- NeurIPS deep inverse workshop—0
Memory-efficient Learning for Large-scale Computational Imaging—0
Memory Efficient Patch-based Training for INR-based GANs—0
Memory-Efficient Super-Resolution of 3D Micro-CT Images Using Octree-Based GANs: Enhancing Resolution and Segmentation Accuracy—0
Memory-Friendly Scalable Super-Resolution via Rewinding Lottery Ticket Hypothesis—0
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks—0
Convolutional neural network based on sparse graph attention mechanism for MRI super-resolution—0
Mesoscopic Facial Geometry Inference Using Deep Neural Networks—0
Metadata-Based RAW Reconstruction via Implicit Neural Functions—0
Convolutional Low-Resolution Fine-Grained Classification—0
Convolutional Bipartite Attractor Networks—0
Convergent plug-and-play with proximal denoiser and unconstrained regularization parameter—0
Meta-learning Slice-to-Volume Reconstruction in Fetal Brain MRI using Implicit Neural Representations—0
Controlling Neural Networks via Energy Dissipation—0
Contrastive Learning for Climate Model Bias Correction and Super-Resolution—0
Transformer-Driven Inverse Problem Transform for Fast Blind Hyperspectral Image Dehazing—0
Metric Imitation by Manifold Transfer for Efficient Vision Applications—0
Contrast: A Hybrid Architecture of Transformers and State Space Models for Low-Level Vision—0
MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN—0
MFSR-GAN: Multi-Frame Super-Resolution with Handheld Motion Modeling—0
MFSR: Multi-fractal Feature for Super-resolution Reconstruction with Fine Details Recovery—0
Continuous Space-Time Video Super-Resolution Utilizing Long-Range Temporal Information—0
Micro CT Image-Assisted Cross Modality Super-Resolution of Clinical CT Images Utilizing Synthesized Training Dataset—0
Micro-CT Synthesis and Inner Ear Super Resolution via Generative Adversarial Networks and Bayesian Inference—0
Continuous Sign Language Recognition via Temporal Super-Resolution Network—0
Mid-wave infrared super-resolution imaging based on compressive calibration and sampling—0
Millimetre-wave Radar for Low-Cost 3D Imaging: A Performance Study—0
Mimic3D: Thriving 3D-Aware GANs via 3D-to-2D Imitation—0
MIMRS: A Survey on Masked Image Modeling in Remote Sensing—0
Continual Learning-Aided Super-Resolution Scheme for Channel Reconstruction and Generalization in OFDM Systems—0
A Comprehensive Survey of Transformers for Computer Vision—0
Transformers in Vision: A Survey—0
MIRE: Matched Implicit Neural Representations—0
Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging—0
Context Reasoning Attention Network for Image Super-Resolution—0
Mitigating Channel-wise Noise for Single Image Super Resolution—0
Mixture-Net: Low-Rank Deep Image Prior Inspired by Mixture Models for Spectral Image Recovery—0
A comprehensive review on Plant Leaf Disease detection using Deep learning—0
A Comprehensive Review of Deep Learning-based Single Image Super-resolution—0
Content-decoupled Contrastive Learning-based Implicit Degradation Modeling for Blind Image Super-Resolution—0
MMAD-Purify: A Precision-Optimized Framework for Efficient and Scalable Multi-Modal Attacks—0
Translation-based Video-to-Video Synthesis—0
MMSR: Multiple-Model Learned Image Super-Resolution Benefiting From Class-Specific Image Priors—0
Content-Aware Local GAN for Photo-Realistic Super-Resolution—0
MNSRNet: Multimodal Transformer Network for 3D Surface Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified