Deep learning approaches for data augmentation in medical imaging: a review
A Kebaili, J Lapuyade-Lahorgue, S Ruan - Journal of Imaging, 2023 - mdpi.com
Deep learning has become a popular tool for medical image analysis, but the limited
availability of training data remains a major challenge, particularly in the medical field where …
availability of training data remains a major challenge, particularly in the medical field where …
A review on generative adversarial networks for image generation
VLT De Souza, BAD Marques, HC Batagelo… - Computers & …, 2023 - Elsevier
Abstract Generative Adversarial Networks (GANs) are a type of deep learning architecture
that uses two networks namely a generator and a discriminator that, by competing against …
that uses two networks namely a generator and a discriminator that, by competing against …
Scaling up gans for text-to-image synthesis
The recent success of text-to-image synthesis has taken the world by storm and captured the
general public's imagination. From a technical standpoint, it also marked a drastic change in …
general public's imagination. From a technical standpoint, it also marked a drastic change in …
Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation
In addition to the unprecedented ability in imaginary creation, large text-to-image models are
expected to take customized concepts in image generation. Existing works generally learn …
expected to take customized concepts in image generation. Existing works generally learn …
Dreambooth3d: Subject-driven text-to-3d generation
We present DreamBooth3D, an approach to personalize text-to-3D generative models from
as few as 3-6 casually captured images of a subject. Our approach combines recent …
as few as 3-6 casually captured images of a subject. Our approach combines recent …
Ablating concepts in text-to-image diffusion models
Large-scale text-to-image diffusion models can generate high-fidelity images with powerful
compositional ability. However, these models are typically trained on an enormous amount …
compositional ability. However, these models are typically trained on an enormous amount …
Adversarial diffusion distillation
A Sauer, D Lorenz, A Blattmann… - arXiv preprint arXiv …, 2023 - arxiv.org
We introduce Adversarial Diffusion Distillation (ADD), a novel training approach that
efficiently samples large-scale foundational image diffusion models in just 1-4 steps while …
efficiently samples large-scale foundational image diffusion models in just 1-4 steps while …
Controlvideo: Training-free controllable text-to-video generation
Text-driven diffusion models have unlocked unprecedented abilities in image generation,
whereas their video counterpart still lags behind due to the excessive training cost of …
whereas their video counterpart still lags behind due to the excessive training cost of …
One-step diffusion with distribution matching distillation
Diffusion models generate high-quality images but require dozens of forward passes. We
introduce Distribution Matching Distillation (DMD) a procedure to transform a diffusion model …
introduce Distribution Matching Distillation (DMD) a procedure to transform a diffusion model …
Localizing object-level shape variations with text-to-image diffusion models
Text-to-image models give rise to workflows which often begin with an exploration step,
where users sift through a large collection of generated images. The global nature of the text …
where users sift through a large collection of generated images. The global nature of the text …