[HTML][HTML] Automated data processing and feature engineering for deep learning and big data applications: a survey

A Mumuni, F Mumuni - Journal of Information and Intelligence, 2024‏ - Elsevier
Modern approach to artificial intelligence (AI) aims to design algorithms that learn directly
from data. This approach has achieved impressive results and has contributed significantly …

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 …

Instruct-nerf2nerf: Editing 3d scenes with instructions

A Haque, M Tancik, AA Efros… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
We propose a method for editing NeRF scenes with text-instructions. Given a NeRF of a
scene and the collection of images used to reconstruct it, our method uses an image …

Adding conditional control to text-to-image diffusion models

L Zhang, A Rao, M Agrawala - Proceedings of the IEEE/CVF …, 2023‏ - openaccess.thecvf.com
We present ControlNet, a neural network architecture to add spatial conditioning controls to
large, pretrained text-to-image diffusion models. ControlNet locks the production-ready large …

Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models

H Chefer, Y Alaluf, Y Vinker, L Wolf… - ACM transactions on …, 2023‏ - dl.acm.org
Recent text-to-image generative models have demonstrated an unparalleled ability to
generate diverse and creative imagery guided by a target text prompt. While revolutionary …

Erasing concepts from diffusion models

R Gandikota, J Materzynska… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Motivated by concerns that large-scale diffusion models can produce undesirable output
such as sexually explicit content or copyrighted artistic styles, we study erasure of specific …

Muse: Text-to-image generation via masked generative transformers

H Chang, H Zhang, J Barber, AJ Maschinot… - arxiv preprint arxiv …, 2023‏ - arxiv.org
We present Muse, a text-to-image Transformer model that achieves state-of-the-art image
generation performance while being significantly more efficient than diffusion or …

Multi-concept customization of text-to-image diffusion

N Kumari, B Zhang, R Zhang… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
While generative models produce high-quality images of concepts learned from a large-
scale database, a user often wishes to synthesize instantiations of their own concepts (for …

Plug-and-play diffusion features for text-driven image-to-image translation

N Tumanyan, M Geyer, S Bagon… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Large-scale text-to-image generative models have been a revolutionary breakthrough in the
evolution of generative AI, synthesizing diverse images with highly complex visual concepts …

Instructpix2pix: Learning to follow image editing instructions

T Brooks, A Holynski, AA Efros - Proceedings of the IEEE …, 2023‏ - openaccess.thecvf.com
We propose a method for editing images from human instructions: given an input image and
a written instruction that tells the model what to do, our model follows these instructions to …