Papers with Code 아카이브

Image Reconstruction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

5

평가표

8

보존된 평가 기록

35

코드

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

https://github.com/esizikova/medsynth_public

공식 코드

Improving Computed Tomography (CT) Reconstruction via 3D Shape Induction

https://github.com/etienne-monier/2020-Ultramicro-fast

공식 코드

Fast reconstruction of atomic-scale STEM-EELS images from sparse sampling

https://github.com/ezioby/padinv

공식 코드

High-fidelity GAN Inversion with Padding Space

https://github.com/fabianbalsiger/mrf-reconstruction-media2020

공식 코드

Spatially Regularized Parametric Map Reconstruction for Fast Magnetic Resonance Fingerprinting

https://github.com/fabianbalsiger/mrf-reconstruction-mlmir2020

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Learning Bloch Simulations for MR Fingerprinting by Invertible Neural Networks

https://github.com/facebookresearch/active-mri-acquisition

공식 코드

Active MR k-space Sampling with Reinforcement Learning

https://github.com/facebookresearch/dynadiff

공식 코드

Dynadiff: Single-stage Decoding of Images from Continuously Evolving fMRI

https://github.com/facebookresearch/fastMRI

공식 코드

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

https://github.com/faebstn96/helix2fan

공식 코드

On the Benefit of Dual-domain Denoising in a Self-supervised Low-dose CT Setting

https://github.com/fair-umn/fair-umn-hgcal

공식 코드

Electron Energy Regression in the CMS High-Granularity Calorimeter Prototype

https://github.com/fan-pixel/ur2p-dehaze

공식 코드

UR2P-Dehaze: Learning a Simple Image Dehaze Enhancer via Unpaired Rich Physical Prior

https://github.com/fanxiaohong/CGPD-CSNet

공식 코드

An Interpretable MRI Reconstruction Network with Two-grid-cycle Correction and Geometric Prior Distillation

https://github.com/fanxiaohong/Deep-Geometric-Distillation-Network-for-CS-MRI

공식 코드

Deep Geometric Distillation Network for Compressive Sensing MRI

https://github.com/fanxiaohong/Nest-DGIL

공식 코드

Nest-DGIL: Nesterov-optimized Deep Geometric Incremental Learning for CS Image Reconstruction

https://github.com/fanxiaohong/mvms-rcn

공식 코드

MVMS-RCN: A Dual-Domain Unfolding CT Reconstruction with Multi-sparse-view and Multi-scale Refinement-correction

https://github.com/fau-lms/dgnet

공식 코드

Cross Spectral Image Reconstruction Using a Deep Guided Neural Network

https://github.com/fau-lms/hyvid

공식 코드

Synthetic Hyperspectral Array Video Database with Applications to Cross-Spectral Reconstruction and Hyperspectral Video Coding

https://github.com/fcaliva/fastMRI_BB_abnormalities_annotation

공식 코드

Adversarial Robust Training of Deep Learning MRI Reconstruction Models

https://github.com/fengyi233/ViPOcc

공식 코드

ViPOcc: Leveraging Visual Priors from Vision Foundation Models for Single-View 3D Occupancy Prediction

https://github.com/fengyiwu98/rpcanet

공식 코드

RPCANet: Deep Unfolding RPCA Based Infrared Small Target Detection

https://github.com/fmerizzi/Deep_image_prior_inpainting_of_ancient_frescoes

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Deep image prior inpainting of ancient frescoes in the Mediterranean Alpine arc

https://github.com/foundationvision/llamagen

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Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

https://github.com/fudanvi/fudanocr

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Orientation-Independent Chinese Text Recognition in Scene Images

https://github.com/fze0012/mr-ccsnet

공식 코드

Global Sensing and Measurements Reuse for Image Compressed Sensing

https://github.com/fzimmermann89/cmrxrecon

공식 코드

NoSENSE: Learned unrolled cardiac MRI reconstruction without explicit sensitivity maps

https://github.com/fzimmermann89/pinqi

공식 코드

PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction

https://github.com/gabrieleilertsen/hdrcnn

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HDR image reconstruction from a single exposure using deep CNNs

https://github.com/gayathrimatcha/sft-kd-recon

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SFT-KD-Recon: Learning a Student-friendly Teacher for Knowledge Distillation in Magnetic Resonance Image Reconstruction

https://github.com/genforce/mganprior

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Image Processing Using Multi-Code GAN Prior

https://github.com/gewelsji/mvlt

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Masked Vision-Language Transformer in Fashion

https://github.com/ghfkahfk/EMResformer

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Iterative Optimal Attention and Local Model for Single Image Rain Streak Removal

https://github.com/giant-pandada/sib-acs_cvpr2025

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Sampling Innovation-Based Adaptive Compressive Sensing

https://github.com/gistvision/e2sri

공식 코드

Learning to Super Resolve Intensity Images from Events

https://github.com/gluucose/pccgan

공식 코드

Image2Points:A 3D Point-based Context Clusters GAN for High-Quality PET Image Reconstruction

https://github.com/goddesshs/transmrsr

공식 코드

TransMRSR: Transformer-based Self-Distilled Generative Prior for Brain MRI Super-Resolution

https://github.com/goeblr/speckle2speckle

공식 코드

Speckle2Speckle: Unsupervised Learning of Ultrasound Speckle Filtering Without Clean Data

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