Papers with Code 아카이브

Image-to-Image Translation

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하위 태스크: 11
평가표: 38
보존된 평가 기록: 195

Image-to-Image Translation is a task in computer vision and machine learning where the goal is to learn a mapping between an input image and an output image, such that the output image can be used to perform a specific task, such as style transfer, data augmentation, or image restoration.

<span style="color:grey; opacity: 0.6">( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )</span>

코드

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

https://github.com/lucatirel/pix2pix-wgangp

공식 코드

Novel Hybrid Integrated Pix2Pix and WGAN Model with Gradient Penalty for Binary Images Denoising

https://github.com/lukemelas/pixmatch

공식 코드

PixMatch: Unsupervised Domain Adaptation via Pixelwise Consistency Training

https://github.com/luyvlei/BiSMAPs

공식 코드

Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic Segmentation

https://github.com/machinevision-seoultech/evci

공식 코드

Image-to-Image Translation-based Data Augmentation for Robust EV Charging Inlet Detection

https://github.com/mahfuzmohammad/brainomaly

공식 코드

Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images

https://github.com/mahfuzmohammad/healthygan

공식 코드

HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease

https://github.com/manugar/imagestyletransfer

공식 코드

Neural Style Transfer and Unpaired Image-to-Image Translation to deal with the Domain Shift Problem on Spheroid Segmentation

https://github.com/mariiadrozdova/diffusion-for-sources-characterisation

공식 코드

Radio-astronomical Image Reconstruction with Conditional Denoising Diffusion Model

https://github.com/matansel/pix2vertex

공식 코드

Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation

https://github.com/matt-bendel/rcgan

공식 코드

A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems

https://github.com/matteomaspero/overview_sct

공식 코드

Deep learning-based synthetic-CT generation in radiotherapy and PET: a review

https://github.com/mazurowski-lab/RaD

공식 코드

Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets

https://github.com/mazurowski-lab/medical-image-similarity-metrics

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Fréchet Radiomic Distance (FRD): A Versatile Metric for Comparing Medical Imaging Datasets

https://github.com/mbanani/novelviewpoints

공식 코드

Novel Object Viewpoint Estimation through Reconstruction Alignment

https://github.com/mchong6/GANsNRoses

공식 코드

GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation (works for videos too!)

https://github.com/mchong6/SOAT

공식 코드

StyleGAN of All Trades: Image Manipulation with Only Pretrained StyleGAN

https://github.com/merlresearch/SteeredDiffusion

공식 코드

Steered Diffusion: A Generalized Framework for Plug-and-Play Conditional Image Synthesis

https://github.com/meteahishali/ada-net

공식 코드

ADA-Net: Attention-Guided Domain Adaptation Network with Contrastive Learning for Standing Dead Tree Segmentation Using Aerial Imagery

https://github.com/meteahishali/r2c-gan

공식 코드

R2C-GAN: Restore-to-Classify Generative Adversarial Networks for Blind X-Ray Restoration and COVID-19 Classification

https://github.com/microsoft/AcousticScatteringData

공식 코드

Fast acoustic scattering using convolutional neural networks

https://github.com/microsoft/CoCosNet-v2

공식 코드

CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation

https://github.com/microsoft/ProDA

공식 코드

Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation

https://github.com/mid-push/irwgan

공식 코드

Unaligned Image-to-Image Translation by Learning to Reweight

https://github.com/miemieyanga/ResiDualGAN-DRDG

공식 코드

ResiDualGAN: Resize-Residual DualGAN for Cross-Domain Remote Sensing Images Semantic Segmentation

https://github.com/mil-tokyo/MCD_DA

공식 코드

Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

https://github.com/mindspore-ai/models/tree/master/research/cv/TokenFusion

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Multimodal Token Fusion for Vision Transformers

https://github.com/mindspore-lab/mindediting

공식 코드

Tunable Convolutions with Parametric Multi-Loss Optimization

https://github.com/mingyuliutw/CoGAN

공식 코드

Coupled Generative Adversarial Networks

https://github.com/mingyuliutw/UNIT

공식 코드

Unsupervised Image-to-Image Translation Networks

https://github.com/mirthai/fast-ddpm

공식 코드

Fast-DDPM: Fast Denoising Diffusion Probabilistic Models for Medical Image-to-Image Generation

https://github.com/misaliet/seamless-satellite-image-synthesis

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Seamless Satellite-image Synthesis

https://github.com/mit-acl/dc2g

공식 코드

Planning Beyond the Sensing Horizon Using a Learned Context

https://github.com/mlandcv/Auxilliary_Reconstruction_GAN

공식 코드

Unsupervised Image Translation using Adversarial Networks for Improved Plant Disease Recognition

https://github.com/mlvlab/scdm

공식 코드

Stochastic Conditional Diffusion Models for Robust Semantic Image Synthesis

https://github.com/mobaidoctor/med-ddpm

공식 코드

Conditional Diffusion Models for Semantic 3D Brain MRI Synthesis

https://github.com/mohammadrsalmanpour/allmetrics-a-unified-python-library-for-standardized-metric-evaluation-in-machine-learning

공식 코드

AllMetrics: A Unified Python Library for Standardized Metric Evaluation and Robust Data Validation in Machine Learning

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