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Image-to-Image Translation
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- 평가표
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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>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Consistency Diffusion Bridge Models
Deep Generative Models for 3D Medical Image Synthesis
AdaDiffSR: Adaptive Region-aware Dynamic Acceleration Diffusion Model for Real-World Image Super-Resolution
A Wavelet Diffusion GAN for Image Super-Resolution
EBDM: Exemplar-guided Image Translation with Brownian-bridge Diffusion Models
DifFRelight: Diffusion-Based Facial Performance Relighting
Image Enhancement Based on Histogram-Guided Multiple Transformation Function Estimation
Improving Object Detection via Local-global Contrastive Learning
Scalable Simulation-free Entropic Unbalanced Optimal Transport
PixelShuffler: A Simple Image Translation Through Pixel Rearrangement
Improving Neural Optimal Transport via Displacement Interpolation
SinoSynth: A Physics-based Domain Randomization Approach for Generalizable CBCT Image Enhancement
Pix2Next: Leveraging Vision Foundation Models for RGB to NIR Image Translation
Enhanced Unsupervised Image-to-Image Translation Using Contrastive Learning and Histogram of Oriented Gradients
I2I-Galip: Unsupervised Medical Image Translation Using Generative Adversarial CLIP
CUNSB-RFIE: Context-aware Unpaired Neural Schr"{o}dinger Bridge in Retinal Fundus Image Enhancement
Image-to-Image Translation Based on Deep Generative Modeling for Radiotherapy Synthetic Dataset Creation
Cross-modality image synthesis from TOF-MRA to CTA using diffusion-based models
Embedded Image-to-Image Translation for Efficient Sim-to-Real Transfer in Learning-based Robot-Assisted Soft Manipulation
Cross-conditioned Diffusion Model for Medical Image to Image Translation
Diffusion-Based Image-to-Image Translation by Noise Correction via Prompt Interpolation
360PanT: Training-Free Text-Driven 360-Degree Panorama-to-Panorama Translation
Multi-scale decomposition of sea surface height snapshots using machine learning
LSE-NeRF: Learning Sensor Modeling Errors for Deblured Neural Radiance Fields with RGB-Event Stereo
Seed-to-Seed: Image Translation in Diffusion Seed Space
CycleGAN with Better Cycles
Reliable Multi-modal Medical Image-to-image Translation Independent of Pixel-wise Aligned Data
Fashion Image-to-Image Translation for Complementary Item Retrieval
FQGA-single: Towards Fewer Training Epochs and Fewer Model Parameters for Image-to-Image Translation Tasks
Conditional Brownian Bridge Diffusion Model for VHR SAR to Optical Image Translation
The Dawn of KAN in Image-to-Image (I2I) Translation: Integrating Kolmogorov-Arnold Networks with GANs for Unpaired I2I Translation
An Analysis for Image-to-Image Translation and Style Transfer
Static IR Drop Prediction with Attention U-Net and Saliency-Based Explainability
Advancing H&E-to-IHC Stain Translation in Breast Cancer: A Multi-Magnification and Attention-Based Approach
FBSDiff: Plug-and-Play Frequency Band Substitution of Diffusion Features for Highly Controllable Text-Driven Image Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.