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/charwing10/isbi2019miccan

공식 코드

MRI Reconstruction via Cascaded Channel-wise Attention Network

https://github.com/chenhu96/self-supervised-mri-reconstruction

공식 코드

Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework

https://github.com/chenkang455/spikeclip

공식 코드

Rethinking High-speed Image Reconstruction Framework with Spike Camera

https://github.com/chenkang455/usp-gaussian

공식 코드

USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting

https://github.com/chenyilan/Y-Net

공식 코드

Y-Net: A Hybrid Deep Learning Reconstruction Framework for Photoacoustic Imaging in vivo

https://github.com/cherise215/Cooperative_Training_and_Latent_Space_Data_Augmentation

공식 코드

Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation

https://github.com/chh11/mgir

공식 코드

Mixed-granularity Implicit Representation for Continuous Hyperspectral Compressive Reconstruction

https://github.com/chohoonhee/ev-lafor

공식 코드

Label-Free Event-based Object Recognition via Joint Learning with Image Reconstruction from Events

https://github.com/chongwang1024/pdac

공식 코드

Progressive Divide-and-Conquer via Subsampling Decomposition for Accelerated MRI

https://github.com/chrisdcs/LAMA-Learned-Alternating-Minimization-Algorithm

공식 코드

Learned Alternating Minimization Algorithm for Dual-domain Sparse-View CT Reconstruction

https://github.com/chunmeifeng/Dual-OctConv

공식 코드

Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction

https://github.com/chunmeifeng/MTrans

공식 코드

Multi-Modal Transformer for Accelerated MR Imaging

https://github.com/chunmeifeng/T2Net

공식 코드

Task Transformer Network for Joint MRI Reconstruction and Super-Resolution

https://github.com/chunmeifeng/fedmri

공식 코드

Specificity-Preserving Federated Learning for MR Image Reconstruction

https://github.com/chunmeifeng/fedpr

공식 코드

Learning Federated Visual Prompt in Null Space for MRI Reconstruction

https://github.com/chunmeifeng/manet

공식 코드

Deep multi-modal aggregation network for MR image reconstruction with auxiliary modality

https://github.com/chunmeifeng/mario

공식 코드

Deep multi-modal aggregation network for MR image reconstruction with auxiliary modality

https://github.com/chxy95/genlv

공식 코드

Learning A Low-Level Vision Generalist via Visual Task Prompt

https://github.com/ciampluca/diffusion_semi_supervised_biomedical_image_segmentation

공식 코드

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

https://github.com/cicwi/WalnutReconstructionCodes

공식 코드

A Cone-Beam X-Ray CT Data Collection designed for Machine Learning

https://github.com/cjf8899/CDRL

공식 코드

Unsupervised Change Detection Based on Image Reconstruction Loss

https://github.com/ckczzj/pdae

공식 코드

Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models

https://github.com/clementchadebec/benchmark_VAE

공식 코드

Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case

https://github.com/clyons19/CG-Net

공식 코드

A Compound Gaussian Least Squares Algorithm and Unrolled Network for Linear Inverse Problems

https://github.com/clyons19/dr-cg-net

공식 코드

Deep Regularized Compound Gaussian Network for Solving Linear Inverse Problems

https://github.com/cmrxrecon/cmrxrecon2024

공식 코드

CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI

https://github.com/cnes/decloud

공식 코드

Comparison of convolutional neural networks for cloudy optical images reconstruction from single or multitemporal joint SAR and optical images

https://github.com/coldrainyht/caffe_dr2

공식 코드

DR2-Net: Deep Residual Reconstruction Network for Image Compressive Sensing

https://github.com/comedialkb/learning_with_passive_optical_nonlinear_mapping

공식 코드

Nonlinear optical encoding enabled by recurrent linear scattering

https://github.com/cpeng93/diffuserecon

공식 코드

Towards performant and reliable undersampled MR reconstruction via diffusion model sampling

https://github.com/cq615/kt-Dynamic-MRI-Reconstruction

공식 코드

Complementary Time-Frequency Domain Networks for Dynamic Parallel MR Image Reconstruction

https://github.com/crossmodalgroup/maskedvectorquantization

공식 코드

Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation

https://github.com/crosszamirski/guided-i2i

공식 코드

Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels

https://github.com/cschenxiang/drsformer

공식 코드

Learning A Sparse Transformer Network for Effective Image Deraining

https://github.com/cschenxiang/nerd-rain

공식 코드

Bidirectional Multi-Scale Implicit Neural Representations for Image Deraining

https://github.com/cschenxiang/udr-mixer

공식 코드

Towards Ultra-High-Definition Image Deraining: A Benchmark and An Efficient Method

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