What are the strengths and weaknesses of the diffusion models?

Answer 1

Diffusion models are strong in generating high-quality, diverse images and capturing complex data distributions, making them effective in tasks like image synthesis and inpainting. Their iterative refinement process allows for fine detail enhancement, resulting in high-resolution outputs. However, they can be computationally intensive and slower compared to other generative models, such as GANs, requiring significant resources for training and inference. Additionally, their performance can be sensitive to the choice of hyperparameters and training data quality.