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 3741–3750 of 3874 papers

TitleStatusHype
Temporal Consistency Learning of inter-frames for Video Super-ResolutionCode0
DeepLight: Reconstructing High-Resolution Observations of Nighttime Light With Multi-Modal Remote Sensing DataCode0
Resolution-invariant Person Re-IdentificationCode0
High-throughput, high-resolution registration-free generated adversarial network microscopyCode0
ResSR: A Computationally Efficient Residual Approach to Super-Resolving Multispectral ImagesCode0
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise ModulationsCode0
High-Resolution GAN Inversion for Degraded Images in Large Diverse DatasetsCode0
High-Quality Face Image SR Using Conditional Generative Adversarial NetworksCode0
Rethinking CNN-Based Pansharpening: Guided Colorization of Panchromatic Images via GANsCode0
High-Frequency Prior-Driven Adaptive Masking for Accelerating Image Super-ResolutionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified