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 1276–1300 of 3874 papers

TitleStatusHype
Data-driven Super-Resolution of Flood Inundation Maps using Synthetic SimulationsCode0
Deep EEG Super-Resolution: Upsampling EEG Spatial Resolution with Generative Adversarial Networks—0
Quaternion-Hadamard Network: A Novel Defense Against Adversarial Attacks with a New Dataset—0
Image Super-Resolution with Guarantees via Conformalized Generative Models—0
Rapid Whole Brain Motion-robust Mesoscale In-vivo MR Imaging using Multi-scale Implicit Neural Representation—0
Spatial Degradation-Aware and Temporal Consistent Diffusion Model for Compressed Video Super-Resolution—0
A Survey of Representation Learning, Optimization Strategies, and Applications for Omnidirectional Vision—0
Fast Omni-Directional Image Super-Resolution: Adapting the Implicit Image Function with Pixel and Semantic-Wise Spherical Geometric PriorsCode0
AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution—0
DiffNMR3: Advancing NMR Resolution Beyond Instrumental Limits—0
DC-VSR: Spatially and Temporally Consistent Video Super-Resolution with Video Diffusion Prior—0
Bridging high resolution sub-cellular imaging with physiologically relevant engineered tissues—0
A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers—0
Low Resource Video Super-resolution using Memory and Residual Deformable Convolutions—0
Exploring Linear Attention Alternative for Single Image Super-ResolutionCode0
Rethinking the Upsampling Layer in Hyperspectral Image Super Resolution—0
Depth Separable architecture for Sentinel-5P Super-Resolution—0
MR imaging in the low-field: Leveraging the power of machine learning—0
Directing Mamba to Complex Textures: An Efficient Texture-Aware State Space Model for Image Restoration—0
Compensation based Dictionary Transfer for Similar Multispectral Image Spectral Super-resolution—0
Spatial-Angular Representation Learning for High-Fidelity Continuous Super-Resolution in Diffusion MRI—0
Solving Turbulent Rayleigh-Bénard Convection using Fourier Neural OperatorsCode0
CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual InferenceCode0
Can Location Embeddings Enhance Super-Resolution of Satellite Imagery?—0
Dfilled: Repurposing Edge-Enhancing Diffusion for Guided DSM Void Filling—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified