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 2101–2110 of 3874 papers

TitleStatusHype
Depth-Independent Depth Completion via Least Square Estimation—0
A Novel Dual Dense Connection Network for Video Super-resolution—0
Adaptive Cross-Layer Attention for Image RestorationCode1
HyperTransformer: A Textural and Spectral Feature Fusion Transformer for PansharpeningCode1
Ad2Attack: Adaptive Adversarial Attack on Real-Time UAV TrackingCode1
Fast Neural Architecture Search for Lightweight Dense Prediction Networks—0
Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed ObservationsCode1
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence—0
Fine-grained Urban Flow Inference with Incomplete DataCode0
Thermographic detection of internal defects using 2D photothermal super resolution reconstruction with sequential laser heating—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified