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

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Showing 1226–1250 of 3874 papers

TitleStatusHype
Semantic-Guided Global-Local Collaborative Networks for Lightweight Image Super-ResolutionCode0
Variational Message Passing-based Multiobject Tracking for MIMO-Radars using Raw Sensor Signals—0
Toward task-driven satellite image super-resolution—0
Involution and BSConv Multi-Depth Distillation Network for Lightweight Image Super-Resolution—0
The Power of Context: How Multimodality Improves Image Super-Resolution—0
CTSR: Controllable Fidelity-Realness Trade-off Distillation for Real-World Image Super Resolution—0
SIR-DIFF: Sparse Image Sets Restoration with Multi-View Diffusion Model—0
RainScaleGAN: a Conditional Generative Adversarial Network for Rainfall DownscalingCode0
A super-resolution reconstruction method for lightweight building images based on an expanding feature modulation network—0
Rethinking Image Evaluation in Super-Resolution—0
C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales—0
Fourier Neural Operator based surrogates for CO_2 storage in realistic geologies—0
ReCamMaster: Camera-Controlled Generative Rendering from A Single Video—0
ECLARE: Efficient cross-planar learning for anisotropic resolution enhancementCode0
FourierSR: A Fourier Token-based Plugin for Efficient Image Super-Resolution—0
Dual-domain Modulation Network for Lightweight Image Super-Resolution—0
SASNet: Spatially-Adaptive Sinusoidal Neural Networks—0
SuperCarver: Texture-Consistent 3D Geometry Super-Resolution for High-Fidelity Surface Detail Generation—0
Resolution Invariant Autoencoder—0
Feature Alignment with Equivariant Convolutions for Burst Image Super-Resolution—0
Reconstruct Anything Model: a lightweight foundation model for computational imaging—0
Over-the-Air Time-Frequency Synchronization in Distributed ISAC Systems—0
QUIET-SR: Quantum Image Enhancement Transformer for Single Image Super-Resolution—0
Boosting Diffusion-Based Text Image Super-Resolution Model Towards Generalized Real-World Scenarios—0
AdaptSR: Low-Rank Adaptation for Efficient and Scalable Real-World Super-Resolution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified