SOTAVerified

Image Super-Resolution

Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.

Papers

Showing 2650 of 1589 papers

TitleStatusHype
Trustworthy Image Super-Resolution via Generative PseudoinverseCode0
CLIP-aware Domain-Adaptive Super-Resolution0
HSRMamba: Efficient Wavelet Stripe State Space Model for Hyperspectral Image Super-ResolutionCode0
ORL-LDM: Offline Reinforcement Learning Guided Latent Diffusion Model Super-Resolution Reconstruction0
Super-Resolution Generative Adversarial Networks based Video Enhancement0
Joint Low-level and High-level Textual Representation Learning with Multiple Masking Strategies0
Semantic-Guided Diffusion Model for Single-Step Image Super-ResolutionCode1
High-Frequency Prior-Driven Adaptive Masking for Accelerating Image Super-ResolutionCode0
StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation0
A Fusion-Guided Inception Network for Hyperspectral Image Super-ResolutionCode0
Optimization of Module Transferability in Single Image Super-Resolution: Universality Assessment and Cycle Residual Blocks0
Small Clips, Big Gains: Learning Long-Range Refocused Temporal Information for Video Super-ResolutionCode1
Unaligned RGB Guided Hyperspectral Image Super-Resolution with Spatial-Spectral Concordance0
GuideSR: Rethinking Guidance for One-Step High-Fidelity Diffusion-Based Super-Resolution0
Quaternion Wavelet-Conditioned Diffusion Models for Image Super-Resolution0
Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional NetworkCode0
Predicting Stress in Two-phase Random Materials and Super-Resolution Method for Stress Images by Embedding Physical Information0
Iterative Collaboration Network Guided By Reconstruction Prior for Medical Image Super-Resolution0
DSPO: Direct Semantic Preference Optimization for Real-World Image Super-Resolution0
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: KwaiSR Dataset and Study0
NTIRE 2025 Challenge on Image Super-Resolution (4): Methods and ResultsCode2
TTRD3: Texture Transfer Residual Denoising Dual Diffusion Model for Remote Sensing Image Super-ResolutionCode1
ARAP-GS: Drag-driven As-Rigid-As-Possible 3D Gaussian Splatting Editing with Diffusion Prior0
NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and ResultsCode1
Distillation-Supervised Convolutional Low-Rank Adaptation for Efficient Image Super-ResolutionCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR29.54Unverified
2HMA†PSNR29.51Unverified
3Hi-IR-LPSNR29.49Unverified
4HAT-LPSNR29.47Unverified
5HAT_FIRPSNR29.44Unverified
6DRCTPSNR29.4Unverified
7HATPSNR29.38Unverified
8SwinFIRPSNR29.36Unverified
9CPAT+PSNR29.36Unverified
10CPATPSNR29.34Unverified
#ModelMetricClaimedVerifiedStatus
1DRCT-LPSNR28.16Unverified
2HMA†PSNR28.13Unverified
3Hi-IR-LPSNR28.13Unverified
4HAT-LPSNR28.09Unverified
5HAT_FIRPSNR28.07Unverified
6CPAT+PSNR28.06Unverified
7DRCTPSNR28.06Unverified
8HATPSNR28.05Unverified
9CPATPSNR28.04Unverified
10SwinFIRPSNR28.03Unverified
#ModelMetricClaimedVerifiedStatus
1Hi-IR-LPSNR28.72Unverified
2DRCT-LPSNR28.7Unverified
3HMA†PSNR28.69Unverified
4HAT-LPSNR28.6Unverified
5HAT_FIRPSNR28.43Unverified
6DRCTPSNR28.4Unverified
7HATPSNR28.37Unverified
8CPAT+PSNR28.33Unverified
9CPATPSNR28.22Unverified
10PFTPSNR28.2Unverified