Diffusion
Generates data by learning to reverse a gradual noising process.
Visão geral
A diffusion model learns to remove noise step by step, so that sampling starts from pure noise and arrives at a plausible sample. It solves the training instability of adversarial methods by replacing a two-player game with a single denoising objective. It exists because that objective is stable and covers the data distribution well, which is why it became the dominant approach for image generation.
Grafo de tecnologias
Como Diffusion se liga ao resto do stack.
Usa e depende de
- Neural Network concept Algorithms Diffusion based on Neural Network High ✓ source
Usado por
- Image Generation application Applications Diffusion used by Image Generation High ✓ source
Ferramentas
Software que implementa ou se integra com Diffusion.
Frameworks
Alternativas
Comparações
Comparações detalhadas com as alternativas acima.