Image-to-Image Translation
492 papers with code • 37 benchmarks • 29 datasets
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.
( Image credit: Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks )
Benchmarks
These leaderboards are used to track progress in Image-to-Image Translation
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Libraries
Use these libraries to find Image-to-Image Translation models and implementationsDatasets
Cityscapes
KITTI
ADE20K
CelebA-HQ
SYNTHIA
GTA5
DeepFashion
Perceptual Similarity
AFHQ
COCO-Stuff
Subtasks
Latest papers
Fine-grained Appearance Transfer with Diffusion Models
babahui/fine-grained-appearance-transfer
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A pivotal aspect of our approach is the strategic use of the predicted $x_0$ space by diffusion models within the latent space of diffusion processes.
A deep learning approach for marine snow synthesis and removal
Marine snow, the floating particles in underwater images, severely degrades the visibility and performance of human and machine vision systems.
H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing
gvisani/hpacker
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Accurately modeling protein 3D structure is essential for the design of functional proteins.
Optimal Transport-Guided Conditional Score-Based Diffusion Models
xjtu-xgu/otcs
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Conditional score-based diffusion model (SBDM) is for conditional generation of target data with paired data as condition, and has achieved great success in image translation.
TPSeNCE: Towards Artifact-Free Realistic Rain Generation for Deraining and Object Detection in Rain
We first introduce a Triangular Probability Similarity (TPS) constraint to guide the generated images toward clear and rainy images in the discriminator manifold, thereby minimizing artifacts and distortions during rain generation.
Adaptive Latent Diffusion Model for 3D Medical Image to Image Translation: Multi-modal Magnetic Resonance Imaging Study
jongdory/aldm
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Our model exhibited successful image synthesis across different source-target modality scenarios and surpassed other models in quantitative evaluations tested on multi-modal brain magnetic resonance imaging datasets of four different modalities and an independent IXI dataset.
WAIT: Feature Warping for Animation to Illustration video Translation using GANs
giddyyupp/wait
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Current state-of-the-art video-to-video translation models rely on having a video sequence or a single style image to stylize an input video.
VI-Diff: Unpaired Visible-Infrared Translation Diffusion Model for Single Modality Labeled Visible-Infrared Person Re-identification
In this paper, we propose VI-Diff, a diffusion model that effectively addresses the task of Visible-Infrared person image translation.
Image-to-Image Translation with Deep Reinforcement Learning
Algolzw/SPAC-Deformable-Registration
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The key feature in the RL-I2IT framework is to decompose a monolithic learning process into small steps with a lightweight model to progressively transform a source image successively to a target image.
Masked Discriminators for Content-Consistent Unpaired Image-to-Image Translation
In this work, we show that masking the inputs of a global discriminator for both domains with a content-based mask is sufficient to reduce content inconsistencies significantly.
