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 2551–2575 of 3874 papers

TitleStatusHype
Efficient Video Compression via Content-Adaptive Super-ResolutionCode1
High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal FusionCode1
SDAN: Squared Deformable Alignment Network for Learning Misaligned Optical ZoomCode0
Unsupervised Degradation Representation Learning for Blind Super-ResolutionCode1
RetrievalFuse: Neural 3D Scene Reconstruction with a DatabaseCode1
MR Slice Profile Estimation by Learning to Match Internal Patch DistributionsCode0
Video-Specific Autoencoders for Exploring, Editing and Transmitting Videos—0
Near field Acoustic Holography on arbitrary shapes using Convolutional Neural NetworkCode0
In-Place Scene Labelling and Understanding with Implicit Scene Representation—0
Flow-based Kernel Prior with Application to Blind Super-ResolutionCode1
Omniscient Video Super-Resolution—0
Transitional Learning: Exploring the Transition States of Degradation for Blind Super-resolutionCode1
Best-Buddy GANs for Highly Detailed Image Super-ResolutionCode1
Training a Task-Specific Image Reconstruction Loss—0
D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-ResolutionCode1
Asymmetric CNN for image super-resolutionCode1
Zero-shot super-resolution with a physically-motivated downsampling kernel for endomicroscopy—0
Multi-frame Super-resolution from Noisy Data—0
Designing a Practical Degradation Model for Deep Blind Image Super-ResolutionCode1
JDSR-GAN: Constructing An Efficient Joint Learning Network for Masked Face Super-Resolution—0
Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution—0
Lightweight Image Super-Resolution with Multi-scale Feature Interaction Network—0
UltraSR: Spatial Encoding is a Missing Key for Implicit Image Function-based Arbitrary-Scale Super-ResolutionCode1
Mathematical Theory of Computational Resolution Limit in Multi-dimensions—0
Gauging diffraction patterns: field of view and bandwidth estimation in lensless holography—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified