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 1501–1525 of 3874 papers

TitleStatusHype
Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student LearningCode0
Efficient Integer-Arithmetic-Only Convolutional Neural NetworksCode0
Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid NetworkCode0
A Novel End-To-End Network for Reconstruction of Non-Regularly Sampled Image Data Using Locally Fully Connected LayersCode0
Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational ApproachCode0
Efficient Event Stream Super-Resolution with Recursive Multi-Branch FusionCode0
cGANs with Projection DiscriminatorCode0
Improving Super-Resolution Methods via Incremental Residual LearningCode0
IntraTomo: Self-Supervised Learning-Based Tomography via Sinogram Synthesis and PredictionCode0
CFSNet: Toward a Controllable Feature Space for Image RestorationCode0
Implicit Image-to-Image Schrodinger Bridge for Image RestorationCode0
Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected NetworkCode0
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific SimulationsCode0
Center Smoothing: Certified Robustness for Networks with Structured OutputsCode0
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse CodingCode0
Image Super-resolution via Feature-augmented Random ForestCode0
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate DataCode0
CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual InferenceCode0
Image Super-Resolution via Attention based Back Projection NetworksCode0
Image Super-Resolution via Deep Recursive Residual NetworkCode0
Image Super-Resolution Using a Wavelet-based Generative Adversarial NetworkCode0
Image Super-Resolution Using Dense Skip ConnectionsCode0
Image Super-Resolution via Deterministic-Stochastic Synthesis and Local Statistical RectificationCode0
Edge-Informed Single Image Super-ResolutionCode0
Image Super-Resolution by Neural Texture TransferCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified