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/Francis-Rings/MotionFollower

High-Resolution Image Synthesis with Latent Diffusion Models

https://github.com/GH3927/Pix2Pix-applied-to-cranes

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/GH3927/pix2pix_linemod_duck

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/GabrieleLozupone/LDAE

Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models

https://github.com/HKUNLP/Dream

MaskGIT: Masked Generative Image Transformer

https://github.com/HrishavBakulBarua/Cycle-HDR

LLM-HDR: Bridging LLM-based Perception and Self-Supervision for Unpaired LDR-to-HDR Image Reconstruction

https://github.com/IMAC-projects/Deblurring-PyTorch

A Review of Convolutional Neural Networks for Inverse Problems in Imaging

https://github.com/IMAC-projects/SRN-Deblurring-PyTorch

A Review of Convolutional Neural Networks for Inverse Problems in Imaging

https://github.com/IMPLabUniPr/swin2-mose

SwinFIR: Revisiting the SwinIR with Fast Fourier Convolution and Improved Training for Image Super-Resolution

https://github.com/INOS-soft/AI

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/INOS-soft/Bro-coil

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/INOS-soft/KuE.electo-waffle

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/INOS-soft/Python-Tools

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/IcarusWizard/monodepth-paddle

Unsupervised Monocular Depth Estimation with Left-Right Consistency

https://github.com/IcarusWizard/monodepth2-paddle

Digging Into Self-Supervised Monocular Depth Estimation

https://github.com/ImagingLab/Colorizing-with-GANs

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/JHLew/PerPix

https://github.com/JaguAroo/DASR

Unsupervised Degradation Representation Learning for Blind Super-Resolution

https://github.com/JamesGlare/Neural-Net-LabView-DLL

Deep Bayesian Inversion

https://github.com/JeffFessler/BLIPSrecon

Blind Primed Supervised (BLIPS) Learning for MR Image Reconstruction

https://github.com/JianqiangRen/AAMS

Universal Style Transfer via Feature Transforms

https://github.com/JobQiu/hackrice

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/JuliaTomo/DeepImagePrior.jl

Accelerated MRI with Un-trained Neural Networks

https://github.com/JuliaTomo/DeepReconstruction.jl

Accelerated MRI with Un-trained Neural Networks

https://github.com/KarlXing/RL-Visual-Continuous-Control

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

https://github.com/Kaz-K/unsupervised-brain-abnormality-detection

Learning Global and Local Features of Normal Brain Anatomy for Unsupervised Abnormality Detection

https://github.com/Kso-Ayaka/MS_Paperwithcode/tree/main/Attribute-Aware%20Deep%20Hashing

Attribute-Aware Deep Hashing with Self-Consistency for Large-Scale Fine-Grained Image Retrieval

https://github.com/Kuga23/DL-fastMRI

fastMRI: An Open Dataset and Benchmarks for Accelerated MRI

https://github.com/LAION-AI/phenaki

MaskGIT: Masked Generative Image Transformer

https://github.com/Lebhoryi/learn_monodepth

Unsupervised Monocular Depth Estimation with Left-Right Consistency

https://github.com/LinZhu111/EVSNN

Event-based Video Reconstruction via Potential-assisted Spiking Neural Network

https://github.com/Lornatang/KernelGAN

Blind Super-Resolution Kernel Estimation using an Internal-GAN

https://github.com/Lornatang/PyTorch-CycleGAN

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/Lornatang/SFTMD-PyTorch

Blind Super-Resolution With Iterative Kernel Correction

https://github.com/LucasSheng/avatar-net

Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration

https://github.com/LukasMosser/geogan

Stochastic reconstruction of an oolitic limestone by generative adversarial networks

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