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 1151–1175 of 3874 papers

TitleStatusHype
Blind Facial Image Quality Enhancement using Non-Rigid Semantic Patches—0
AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution—0
An Advanced Features Extraction Module for Remote Sensing Image Super-Resolution—0
Dense U-net for super-resolution with shuffle pooling layer—0
Densely Connected High Order Residual Network for Single Frame Image Super Resolution—0
Blaze3DM: Marry Triplane Representation with Diffusion for 3D Medical Inverse Problem Solving—0
Fast and Light-Weight Network for Single Frame Structured Illumination Microscopy Super-Resolution—0
Dense Dual-Attention Network for Light Field Image Super-Resolution—0
BLADE: Filter Learning for General Purpose Computational Photography—0
FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos—0
Bit-depth color recovery via off-the-shelf super-resolution models—0
A Multi-Task Learning Model for Super Resolution of Wireless Channel Characteristics—0
Fast and Accurate Image Upscaling With Super-Resolution Forests—0
Denoising Diffusion Probabilistic Models for Robust Image Super-Resolution in the Wild—0
Bi-Noising Diffusion: Towards Conditional Diffusion Models with Generative Restoration Priors—0
DEM Super-Resolution with EfficientNetV2—0
Accelerated WGAN update strategy with loss change rate balancing—0
Acceleration-Based Kalman Tracking for Super-Resolution Ultrasound Imaging in vivo—0
Fast and selective super-resolution ultrasound in vivo with sono-switchable nanodroplets—0
Delta-WKV: A Novel Meta-in-Context Learner for MRI Super-Resolution—0
DELTAR: Depth Estimation from a Light-weight ToF Sensor and RGB Image—0
Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds—0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
Degrees of freedom for off-the-grid sparse estimation—0
Binary Neural Networks as a general-propose compute paradigm for on-device computer vision—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified