TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On

TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On

Information Science, Computer Science, Artificial Intelligence,
virtual try-on   fine-grained identity control   diffusion model   training efficiency   clothing identity preservation  

TryOn-Adapter——Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On Research Background and Problem Virtual try-on technology has gained widespread attention in recent years. Its core objective is to seamlessly adjust given clothing onto a specific person while avoiding distortion of the garment’s patterns and textur...

AugDiff: Diffusion-Based Feature Augmentation for Multiple Instance Learning in Whole Slide Image

Information Science, Computer Science, Artificial Intelligence, Medicine, Oncology,
feature augmentation   diffusion model   multiple instance learning   whole slide image   computational pathology   deep learning   image generation  

Diffusion-Based Feature Augmentation: A Novel Approach for Multiple Instance Learning in Whole Slide Images Academic Background and Research Motivation In computational pathology, effectively analyzing Whole Slide Images (WSIs) is a burgeoning area of research. WSIs are ultra-high-resolution images with a broad field of view and are widely employed...

StyleAdapter: A Unified Stylized Image Generation Model

Information Science, Artificial Intelligence,
stylized image generation   AI-generated content   diffusion model   computer vision   text-to-image synthesis  

StyleAdapter: A Unified Stylized Image Generation Model In recent years, advancements in text-to-image (T2I) generation and deep learning models have significantly driven progress in artificial intelligence for image generation. However, integrating specific styles from reference images into high-quality images generated from textual prompts remain...

Diffusion-based Deep Learning Method for Augmenting Ultrastructural Imaging and Volume Electron Microscopy

Diffusion-based Deep Learning Method for Augmenting Ultrastructural Imaging and Volume Electron Microscopy

Information Science, Electronic Information, Artificial Intelligence, Medicine, Medical Imaging, Life Sciences, Cell Biology, Biochemistry, Biophysics,
diffusion model   electron microscopy   volume electron microscopy   high-resolution imaging   deep learning  

Enhancing Super-Resolution Imaging and Volume Electron Microscopy with Deep Learning Algorithms Based on Diffusion Models Background Introduction Electron Microscopy (EM) as a high-resolution imaging tool has made significant breakthroughs in cell biology. Traditional EM techniques are primarily used for two-dimensional imaging, and although they h...

Diffusion Model Optimization with Deep Learning

Diffusion Model Optimization with Deep Learning

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Biophysics,
deep learning   diffusion model   neural network   microstructural imaging   self-supervised learning  

Dimond: A Study on Optimizing Diffusion Models through Deep Learning Academic Background In brain science and clinical applications, Diffusion Magnetic Resonance Imaging (dMRI) is an essential tool for non-invasively mapping the microstructure and neural connectivity of brain tissue. However, accurately estimating parameters of the diffusion signal...

Synthetic Lagrangian Turbulence by Generative Diffusion Models

Physics, Fluid Physics, Information Science, Artificial Intelligence,
turbulence   diffusion model   Lagrangian particles  

Currently, there are significant challenges in studying the statistical and geometrical properties of particles carried by the fluid in turbulence. Despite outstanding efforts in theory, numerical simulations, and experiments over the past 30 years, there is still a lack of models that can realistically reproduce the statistical and topological fea...