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Super-Resolution

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하위 태스크: 7
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/shadyabh/IAGAN

공식 코드

Image-Adaptive GAN based Reconstruction

https://github.com/shallowdream204/SODA-SR

공식 코드

Uncertainty-Aware Source-Free Adaptive Image Super-Resolution with Wavelet Augmentation Transformer

https://github.com/shamanDevel/IsosurfaceSuperresolution

공식 코드

Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution

https://github.com/shamandevel/fv-srn

공식 코드

Fast Neural Representations for Direct Volume Rendering

https://github.com/shangqigao/gsq-image-SR

공식 코드

Multi-scale deep neural networks for real image super-resolution

https://github.com/shangwei5/amsr

공식 코드

High-Frequency Prior-Driven Adaptive Masking for Accelerating Image Super-Resolution

https://github.com/shangwei5/st-avsr

공식 코드

Arbitrary-Scale Video Super-Resolution with Structural and Textural Priors

https://github.com/shank2358/mudet

공식 코드

Multimodal Collaboration Networks for Geospatial Vehicle Detection in Dense, Occluded, and Large-Scale Events

https://github.com/sheqi/GAN_Review

공식 코드

Generative Adversarial Networks in Computer Vision: A Survey and Taxonomy

https://github.com/shermanlian/kbnet

공식 코드

Kernel-aware Burst Blind Super-Resolution

https://github.com/shermanlian/swrn

공식 코드

Sliding Window Recurrent Network for Efficient Video Super-Resolution

https://github.com/shinywang33/esl-net-plusplus

공식 코드

Learning to Super-Resolve Blurry Images with Events

https://github.com/shiwuxuan/suft

공식 코드

Symmetric Uncertainty-Aware Feature Transmission for Depth Super-Resolution

https://github.com/shizenglin/measure-and-control-spectral-bias

공식 코드

On Measuring and Controlling the Spectral Bias of the Deep Image Prior

https://github.com/shlezingerlab/mbdl_book

공식 코드

Model-Based Deep Learning

https://github.com/shreyvish5678/SR-NeRF-with-Variational-Diffusion-Strategies

공식 코드

Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion Strategies

https://github.com/shreyvish5678/advancing-super-resolution-in-neural-radiance-fields-via-variational-diffusion-strategies

공식 코드

Advancing Super-Resolution in Neural Radiance Fields via Variational Diffusion Strategies

https://github.com/shuntama/srdd

공식 코드

Image Super-Resolution with Deep Dictionary

https://github.com/shuohan/espreso2

공식 코드

MR Slice Profile Estimation by Learning to Match Internal Patch Distributions

https://github.com/sichun233746/motif

공식 코드

MoTIF: Learning Motion Trajectories with Local Implicit Neural Functions for Continuous Space-Time Video Super-Resolution

https://github.com/sijieliu518/sgenet

공식 코드

Efficient scene text image super-resolution with semantic guidance

https://github.com/sisrformer/grformer

공식 코드

GRFormer: Grouped Residual Self-Attention for Lightweight Single Image Super-Resolution

https://github.com/sjames40/ugodit

공식 코드

UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights

https://github.com/sleepylin/tasr

공식 코드

TASR: Timestep-Aware Diffusion Model for Image Super-Resolution

https://github.com/slp-rl/aero

공식 코드

AERO: Audio Super Resolution in the Spectral Domain

https://github.com/smilenaxx/rplhr-ct

공식 코드

RPLHR-CT Dataset and Transformer Baseline for Volumetric Super-Resolution from CT Scans

https://github.com/snel-repo/sbtt-demo

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Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time

https://github.com/songluchuan/adasr-talkinghead

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Adaptive Super Resolution For One-Shot Talking-Head Generation

https://github.com/sony/pagoda

공식 코드

PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher

https://github.com/sooyekim/Deep-SR-ITM

공식 코드

Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR Applications

https://github.com/soumickmj/FTSuperResDynMRI

공식 코드

Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge

https://github.com/soumickmj/ddos

공식 코드

DDoS-UNet: Incorporating temporal information using Dynamic Dual-channel UNet for enhancing super-resolution of dynamic MRI

https://github.com/sqyon/MDFN

공식 코드

Multi-Dimension Fusion Network for Light Field Spatial Super-Resolution using Dynamic Filters

https://github.com/sremedios/eclare

공식 코드

ECLARE: Efficient cross-planar learning for anisotropic resolution enhancement

https://github.com/srijamiya/LittleYOLO-SPP

공식 코드

LittleYOLO-SPP: A Delicate Real-Time Vehicle Detection Algorithm

https://github.com/srinivas-512/pnp_nystra

공식 코드

Plug-and-Play Linear Attention for Pre-trained Image and Video Restoration Models

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