Vector quantized diffusion model for text-to-image synthesis
We present the vector quantized diffusion (VQ-Diffusion) model for text-to-image generation.
This method is based on a vector quantized variational autoencoder (VQ-VAE) whose latent …
This method is based on a vector quantized variational autoencoder (VQ-VAE) whose latent …
Knowledge distillation: A survey
In recent years, deep neural networks have been successful in both industry and academia,
especially for computer vision tasks. The great success of deep learning is mainly due to its …
especially for computer vision tasks. The great success of deep learning is mainly due to its …
Dae-gan: Dynamic aspect-aware gan for text-to-image synthesis
Text-to-image synthesis refers to generating an image from a given text description, the key
goal of which lies in photo realism and semantic consistency. Previous methods usually …
goal of which lies in photo realism and semantic consistency. Previous methods usually …
A comprehensive review of generative adversarial networks: Fundamentals, applications, and challenges
In machine learning, a generative model is responsible for generating new samples of data
in terms of a probabilistic model. Generative adversarial network (GAN) has been widely …
in terms of a probabilistic model. Generative adversarial network (GAN) has been widely …
Big data and AI-driven product design: A survey
H Quan, S Li, C Zeng, H Wei, J Hu - Applied Sciences, 2023 - mdpi.com
As living standards improve, modern products need to meet increasingly diversified and
personalized user requirements. Traditional product design methods fall short due to their …
personalized user requirements. Traditional product design methods fall short due to their …
DR-GAN: Distribution regularization for text-to-image generation
This article presents a new text-to-image (T2I) generation model, named distribution
regularization generative adversarial network (DR-GAN), to generate images from text …
regularization generative adversarial network (DR-GAN), to generate images from text …
Faceclip: Facial image-to-video translation via a brief text description
The existing image-to-video translation methods generally follow a frame-by-frame
generative paradigm, while extracting the temporal information from a reference video or an …
generative paradigm, while extracting the temporal information from a reference video or an …
Dse-gan: Dynamic semantic evolution generative adversarial network for text-to-image generation
Text-to-image generation aims at generating realistic images which are semantically
consistent with the given text. Previous works mainly adopt the multi-stage architecture by …
consistent with the given text. Previous works mainly adopt the multi-stage architecture by …
CMAFGAN: A Cross-Modal Attention Fusion based Generative Adversarial Network for attribute word-to-face synthesis
Face synthesis based on attribute words is a novel and challenging topic in computer vision,
which has various application potentials in public security and multimedia. Existing attribute …
which has various application potentials in public security and multimedia. Existing attribute …
RiFeGAN2: Rich feature generation for text-to-image synthesis from constrained prior knowledge
Text-to-image synthesis is a challenging task that generates realistic images from a textual
description. The description contains limited information compared with the corresponding …
description. The description contains limited information compared with the corresponding …