Papers with Code 아카이브

Image-to-Image Translation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/Harry-Thasarathan/TCVC

공식 코드

Automatic Temporally Coherent Video Colorization

https://github.com/HelenMao/MSGAN

공식 코드

Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis

https://github.com/HelenMao/SAVI2I

공식 코드

Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors

https://github.com/HideUnderBush/UI2I_via_StyleGAN2

공식 코드

Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network

https://github.com/Hindawi91/Pseudo_Supervised_Metrics

공식 코드

Domain-knowledge Inspired Pseudo Supervision (DIPS) for Unsupervised Image-to-Image Translation Models to Support Cross-Domain Classification

https://github.com/Honlan/DMT

공식 코드

Disentangled Makeup Transfer with Generative Adversarial Network

https://github.com/HsinYingLee/DRIT

공식 코드

Diverse Image-to-Image Translation via Disentangled Representations

https://github.com/IDKiro/MCT

공식 코드

Multi-Curve Translator for High-Resolution Photorealistic Image Translation

https://github.com/IDKiro/sdxs

공식 코드

SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions

https://github.com/IGLICT/DeepFaceDrawing-Jittor

공식 코드

Deep Generation of Face Images from Sketches

https://github.com/IVRL/ComicsDepth

공식 코드

Estimating Image Depth in the Comics Domain

https://github.com/IshmaelBelghazi/ALI

공식 코드

Adversarially Learned Inference

https://github.com/ItzikMalkiel/AGB

공식 코드

Adaptive Gradient Balancing for UndersampledMRI Reconstruction and Image-to-Image Translation

https://github.com/IyatomiLab/LeafGAN

공식 코드

LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis

https://github.com/JDAI-CV/FADA

공식 코드

Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation

https://github.com/JOP-Lee/READ-Large-Scale-Neural-Scene-Rendering-for-Autonomous-Driving

공식 코드

READ: Large-Scale Neural Scene Rendering for Autonomous Driving

https://github.com/JarrentWu1031/CCPL

공식 코드

CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer

https://github.com/Jian-danai/Decompose-Distill-BeautyGAN

공식 코드

Compressing Facial Makeup Transfer Networks by Collaborative Distillation and Kernel Decomposition

https://github.com/JianghaoWu/FPL-UDA

공식 코드

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation

https://github.com/JunlinHan/CWR

공식 코드

Single Underwater Image Restoration by Contrastive Learning

https://github.com/JunlinHan/DCLGAN

공식 코드

Dual Contrastive Learning for Unsupervised Image-to-Image Translation

https://github.com/KAIST-VICLab/C-DiffSET

공식 코드

C-DiffSET: Leveraging Latent Diffusion for SAR-to-EO Image Translation with Confidence-Guided Reliable Object Generation

https://github.com/KU-CVLAB/InstaFormer

공식 코드

InstaFormer: Instance-Aware Image-to-Image Translation with Transformer

https://github.com/KU-CVLAB/LANIT

공식 코드

LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data

https://github.com/KaimingHe/resnet-1k-layers

공식 코드

Deep Residual Learning for Image Recognition

https://github.com/Kaiseem/AD-GAN

공식 코드

AD-GAN: End-to-end Unsupervised Nuclei Segmentation with Aligned Disentangling Training

https://github.com/Kaminyou/Dense-Normalization

공식 코드

Every Pixel Has its Moments: Ultra-High-Resolution Unpaired Image-to-Image Translation via Dense Normalization

https://github.com/KarlXing/LUSR

공식 코드

Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation

https://github.com/LCAD-UFES/publications-arruda-ijcnn-2019

공식 코드

Cross-Domain Car Detection Using Unsupervised Image-to-Image Translation: From Day to Night

https://github.com/LS4GAN/uvcgan4slats

공식 코드

Unpaired Image Translation to Mitigate Domain Shift in Liquid Argon Time Projection Chamber Detector Responses

https://github.com/MICV-yonsei/CT2MRI

공식 코드

Slice-Consistent 3D Volumetric Brain CT-to-MRI Translation with 2D Brownian Bridge Diffusion Model

https://github.com/MIDA-group/CoMIR

공식 코드

CoMIR: Contrastive Multimodal Image Representation for Registration

https://github.com/MIDA-group/MultiRegEval

공식 코드

Is Image-to-Image Translation the Panacea for Multimodal Image Registration? A Comparative Study

https://github.com/MInner/lrmf

공식 코드

Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment

https://github.com/ML-GSAI/EGSDE

공식 코드

EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations

https://github.com/MRUIL/WDNet

공식 코드

WDNet: Watermark-Decomposition Network for Visible Watermark Removal

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