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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/amanchadha/iSeeBetter

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iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks

https://github.com/amazingren/ntire2024_esr

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The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report

https://github.com/amazingren/ntire2025_esr

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The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report

https://github.com/amhamster/c2pd

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C2PD: Continuity-Constrained Pixelwise Deformation for Guided Depth Super-Resolution

https://github.com/amirdahari1/superres

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Fusion of complementary 2D and 3D mesostructural datasets using generative adversarial networks

https://github.com/anastasiia-kornilova/MMDF

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Deep learning Framework for Mobile Microscopy

https://github.com/andreas128/SRFlow

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SRFlow: Learning the Super-Resolution Space with Normalizing Flow

https://github.com/andreasfloros/trustworthy-super-resolution

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Trustworthy Image Super-Resolution via Generative Pseudoinverse

https://github.com/aneesh3108/AeroRIT

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AeroRIT: A New Scene for Hyperspectral Image Analysis

https://github.com/angelomenezes/Pytorch_Face_SR

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Analysis and evaluation of Deep Learning based Super-Resolution algorithms to improve performance in Low-Resolution Face Recognition

https://github.com/angelvillar96/super-resolution-noisy-images

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Deep learning architectural designs for super-resolution of noisy images

https://github.com/annegnx/PnP-Flow

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PnP-Flow: Plug-and-Play Image Restoration with Flow Matching

https://github.com/anonyr7/Sinogram-Inpainting

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2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network

https://github.com/anshgs/earthgen

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EarthGen: Generating the World from Top-Down Views

https://github.com/anthonymlortiz/epitomes_lsr

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Mining self-similarity: Label super-resolution with epitomic representations

https://github.com/anthonyzhou-1/mae-pdes

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Masked Autoencoders are PDE Learners

https://github.com/antoinedelplace/MRI-Generation

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Segmentation and Generation of Magnetic Resonance Images by Deep Neural Networks

https://github.com/antoinedelplace/MRI-Segmentation

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Segmentation and Generation of Magnetic Resonance Images by Deep Neural Networks

https://github.com/aounon/center-smoothing

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Center Smoothing: Certified Robustness for Networks with Structured Outputs

https://github.com/arashfree/TLW-in-Super-Resolution

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Trainable Loss Weights in Super-Resolution

https://github.com/arcananana/cdcn

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Bridging Component Learning with Degradation Modelling for Blind Image Super-Resolution

https://github.com/arcananana/dssr

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Learning Detail-Structure Alternative Optimization for Blind Super-Resolution

https://github.com/arctichare105/s3diff

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Degradation-Guided One-Step Image Super-Resolution with Diffusion Priors

https://github.com/arsenal9971/poissonnet

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Neural Poisson Surface Reconstruction: Resolution-Agnostic Shape Reconstruction from Point Clouds

https://github.com/arturia-pendragon-iris/hipas_av_segmentation

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Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences

https://github.com/aselsan-research-imaging-team/bicubic-plusplus

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Bicubic++: Slim, Slimmer, Slimmest -- Designing an Industry-Grade Super-Resolution Network

https://github.com/ashj9/AFN

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AFN: Attentional Feedback Network based 3D Terrain Super-Resolution

https://github.com/asindel/VSRF

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Learning from a Handful Volumes: MRI Resolution Enhancement with Volumetric Super-Resolution Forests

https://github.com/augusthoeg/mtvnet

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MTVNet: Mapping using Transformers for Volumes -- Network for Super-Resolution with Long-Range Interactions

https://github.com/aulrichsen/sronn

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Operational Neural Networks for Parameter-Efficient Hyperspectral Single-Image Super-Resolution

https://github.com/aupendu/sr-uncertainty

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Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network

https://github.com/aurangau/ICIP2024

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A Dictionary Based Approach for Removing Out-of-Focus Blur

https://github.com/avc2-uestc/craft-sr

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Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolution

https://github.com/avc2-uestc/frequency-inspired-optimization-for-efficientsr

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Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolution

https://github.com/avinashpaliwal/Deep-SloMo

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Deep Slow Motion Video Reconstruction with Hybrid Imaging System

https://github.com/avisekiit/TCSVT-LightWeight-CNNs

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Lightweight Modules for Efficient Deep Learning based Image Restoration

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