Image Generation with Multimodal Priors using Denoising Diffusion Probabilistic Models. (arXiv:2206.05039v1 [cs.CV])

Image synthesis under multi-modal priors is a useful and challenging task
that has received increasing attention in recent years. A major challenge in
using generative models to accomplish this task is the lack of paired data
containing all modalities (i.e. priors) and corresponding outputs. In recent
work, a variational auto-encoder (VAE) model was trained in a weakly supervised
manner to address this challenge. Since the generative power of VAEs is usually
limited, it is difficult for this method to synthesize …

arxiv cv denoising diffusion generation image image generation multimodal