Latent Space
A low-dimensional feature space in deep learning models that compresses high-dimensional data such as images. Encoders such as VAEs map input data into this space, where computations are performed before decoding back to the original domain, substantially reducing computational cost.
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In the context of this paper, equivariance requires that "first predicting in latent space and then encoding" and "first executing the true transition and then encoding" should yield consistent results.
AI-generated food images often suffer from conceptual confusion issues, such as generating bizarre hybrid products like donut shrimp, stemming from the model causing visual attributes of different objects to interfere with each other in the latent space.
Stable Diffusion moves the diffusion process from pixel space to latent space, compressing images into low-dimensional representations via a VAE encoder before denoising, thereby reducing computational overhead.
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九格网格生成策略能提升一致性，因为九个区域在去噪过程中共享同一个潜在空间的上下文信息
80%UnverifiedStable Diffusion moves the diffusion process from pixel space to latent space, compressing images into low-dimensional representations via a VAE encoder before denoising, thereby reducing computational overhead.
60%UnverifiedIn the context of this paper, equivariance requires that "first predicting in latent space and then encoding" and "first executing the true transition and then encoding" should yield consistent results.
50%UnverifiedAI-generated food images often suffer from conceptual confusion issues, such as generating bizarre hybrid products like donut shrimp, stemming from the model causing visual attributes of different objects to interfere with each other in the latent space.
50%