Papers with Code 아카이브

SSIM

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코드

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

https://github.com/rebeccaeexu/RRID

공식 코드

Image Demoireing in RAW and sRGB Domains

https://github.com/ren-creater/forecast-video-diffmodels

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Improving Tropical Cyclone Forecasting With Video Diffusion Models

https://github.com/renyang-home/alvc

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Advancing Learned Video Compression with In-loop Frame Prediction

https://github.com/rgsl888/U-Finger-A-Fingerprint-Denosing-Network

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U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting

https://github.com/richzhang/PerceptualSimilarity

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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

https://github.com/ruanyudi/ecaformer

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ECAFormer: Low-light Image Enhancement using Cross Attention

https://github.com/ruyi-zha/r2_gaussian

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R$^2$-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction

https://github.com/sabaridsn/MultilevelHyper_Vision_Net

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Moire Image Restoration using Multi Level Hyper Vision Net

https://github.com/sadjadrz/Lung-segmentation-dataset

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FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation

https://github.com/sadjadrz/fusionlungnet

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FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation

https://github.com/safouaneelg/copulasimilarity

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CSIM: A Copula-based similarity index sensitive to local changes for Image quality assessment

https://github.com/samahkh/npb-rec

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NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data

https://github.com/sangyun884/mssr

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Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super Resolution

https://github.com/sarcDV/SSIM-Class-Regression-Brain

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Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images

https://github.com/sayantondibbo/sca

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Improving Robustness to Model Inversion Attacks via Sparse Coding Architectures

https://github.com/seanmullery/SHSM

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A spatial hue similarity measure for assessment of colourisation

https://github.com/sedaboni/ADMM-DIPTV

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Combining Weighted Total Variation and Deep Image Prior for natural and medical image restoration via ADMM

https://github.com/seungho-snu/SROOE

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Perception-Oriented Single Image Super-Resolution using Optimal Objective Estimation

https://github.com/shadowtwin41/brats_2023_2024_solutions

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Brain Tumour Removing and Missing Modality Generation using 3D WDM

https://github.com/shaoyanpan/Full-dose-Whole-body-PET-Synthesis-from-Low-dose-PET-Using-Consistency-Model

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Full-dose Whole-body PET Synthesis from Low-dose PET Using High-efficiency Denoising Diffusion Probabilistic Model: PET Consistency Model

https://github.com/shaoyanpan/Synthetic-CT-generation-from-MRI-using-3D-transformer-based-denoising-diffusion-model

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Synthetic CT Generation from MRI using 3D Transformer-based Denoising Diffusion Model

https://github.com/sharifamit/swin-vftr

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SwinVFTR: A Novel Volumetric Feature-learning Transformer for 3D OCT Fluid Segmentation

https://github.com/shijianjian/ImmersePro

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ImmersePro: End-to-End Stereo Video Synthesis Via Implicit Disparity Learning

https://github.com/shuhongchen/eisai-anime-interpolator

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Improving the Perceptual Quality of 2D Animation Interpolation

https://github.com/sim-2-real/wideband3dgs

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Wideband RF Radiance Field Modeling Using Frequency-embedded 3D Gaussian Splatting

https://github.com/siwangzhou/deepbcs

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Multi-Channel Deep Networks for Block-Based Image Compressive Sensing

https://github.com/skhu101/consistentnerf

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ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis

https://github.com/smbonilla/gaussianpancakes

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Gaussian Pancakes: Geometrically-Regularized 3D Gaussian Splatting for Realistic Endoscopic Reconstruction

https://github.com/smehdia/NTIRE2021-IQA-MACS

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(ASNA) An Attention-based Siamese-Difference Neural Network with Surrogate Ranking Loss function for Perceptual Image Quality Assessment

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

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

https://github.com/soumickmj/FTSuperResDynMRI

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

https://github.com/soumickmj/MRUnder

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ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data

https://github.com/soumickmj/NCC1701

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ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data

https://github.com/soumickmj/ddos

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

https://github.com/sriprabhar/hypercoil-recon

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HyperCoil-Recon: A Hypernetwork-based Adaptive Coil Configuration Task Switching Network for MRI Reconstruction

https://github.com/sriprabhar/km-maml

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Generalizing Supervised Deep Learning MRI Reconstruction to Multiple and Unseen Contrasts using Meta-Learning Hypernetworks

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.