Papers with Code 아카이브

Super-Resolution

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하위 태스크: 6
평가표: 1
보존된 평가 기록: 1

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.

<span style="color:grey; opacity: 0.6">( Credit: MemNet )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/lukazso/kpbms-pvdn

공식 코드

Combining Visual Saliency Methods and Sparse Keypoint Annotations to Providently Detect Vehicles at Night

https://github.com/luohongming/CISR_PSI

공식 코드

Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement

https://github.com/lusinlu/gradient_variance_loss

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Gradient Variance Loss for Structure-Enhanced Image Super-Resolution

https://github.com/lxlscut/Unfolding-ADMM-for-Enhanced-Subspace-Clustering-of-Hyperspectral-Images

공식 코드

Unfolding ADMM for Enhanced Subspace Clustering of Hyperspectral Images

https://github.com/lycexe/structsr

공식 코드

StructSR: Refuse Spurious Details in Real-World Image Super-Resolution

https://github.com/lyh-18/EQVI

공식 코드

Enhanced Quadratic Video Interpolation

https://github.com/lykaust15/DLBI

공식 코드

DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy

https://github.com/lzhengchun/dsgan

공식 코드

Fast and accurate learned multiresolution dynamical downscaling for precipitation

https://github.com/m-lyon/dmri-pcconv

공식 코드

Spatio-Angular Convolutions for Super-resolution in Diffusion MRI

https://github.com/m-lyon/dmri-rcnn

공식 코드

Angular Super-Resolution in Diffusion MRI with a 3D Recurrent Convolutional Autoencoder

https://github.com/magrilab/pisr

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Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems

https://github.com/majedelhelou/SFM

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Stochastic Frequency Masking to Improve Super-Resolution and Denoising Networks

https://github.com/makinyilmaz/dimosr

공식 코드

DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-Resolution

https://github.com/mandalinadagi/wavelettention

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Training Transformer Models by Wavelet Losses Improves Quantitative and Visual Performance in Single Image Super-Resolution

https://github.com/mandalinadagi/wgsr

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Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts

https://github.com/mandt-lab/c-pigdm

공식 코드

Fast Samplers for Inverse Problems in Iterative Refinement Models

https://github.com/mandt-lab/ci2rm

공식 코드

Fast Samplers for Inverse Problems in Iterative Refinement Models

https://github.com/marcelowds/fasr

공식 코드

Multi-Feature Aggregation in Diffusion Models for Enhanced Face Super-Resolution

https://github.com/marcelowds/sr-sde

공식 코드

Face Super-Resolution Using Stochastic Differential Equations

https://github.com/marijavella/hs-sr-tvtv

공식 코드

Enhanced Hyperspectral Image Super-Resolution via RGB Fusion and TV-TV Minimization

https://github.com/marijavella/sr-tvtvsolver

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Single Image Super-Resolution via CNN Architectures and TV-TV Minimization

https://github.com/marijavella/sr-via-CNNs-and-tvtv

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Robust Single-Image Super-Resolution via CNNs and TV-TV Minimization

https://github.com/martenlienen/finite-element-networks

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Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks

https://github.com/matciotola/z-pnn

공식 코드

Pansharpening by convolutional neural networks in the full resolution framework

https://github.com/matheusbarrosp/sr-semseg-end2end

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An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation

https://github.com/matt-bendel/rcgan

공식 코드

A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems

https://github.com/maxjiang93/space_time_pde

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MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework

https://github.com/maxwerhahn/Multi-pass-GAN

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A Multi-Pass GAN for Fluid Flow Super-Resolution

https://github.com/mbkiss/2detectcodes

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2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning

https://github.com/mchatton/w2s-tensorflow

공식 코드

Microscopy Image Restoration using Deep Learning on W2S

https://github.com/mdswyz/SISN-Face-Hallucination

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Face Hallucination via Split-Attention in Split-Attention Network

https://github.com/medical-image-analysis-laboratory/fetmrqc_sr

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Automatic quality control in multi-centric fetal brain MRI super-resolution reconstruction

https://github.com/megvii-research/NAFNet

공식 코드

NAFSSR: Stereo Image Super-Resolution Using NAFNet

https://github.com/megvii-research/d2c-sr

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D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution

https://github.com/megvii-research/dcls-sr

공식 코드

Deep Constrained Least Squares for Blind Image Super-Resolution

https://github.com/megvii-research/wacv2024-safa

공식 코드

Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution

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