In contrast, Stable Diffusion is an open-sourcelatent diffusion modelthat uses text or image prompts to encode a latent representation of the desired image. The latent representation guides the diffusion process to ensure the generated image is statistically similar to the user’s prompt. Midjourney...
What is FLUX.1? FLUX (or FLUX.1) is a suite of text-to-image models from Black Forest Labs, a new company set up by some of the AI researchers behind innovations and models like VQGAN, Stable Diffusion, Latent Diffusion, and Adversarial Diffusion Distillation. The first FLUX models were...
Using unsupervisedmachine learning, autoencoders are trained to discoverlatent variablesof the input data: hidden or random variables that, despite not being directly observable, fundamentally inform the way data is distributed. Collectively, the latent variables of a given set of input data are refer...
Stable Diffusion, however, has its own trick to deal with high-dimensionality. Instead of working with images, its autoencoder element turns them into low-dimension representations. There’s still noise, timesteps, and prompts, but all the U-Net’s processing is done in a compressed latent sp...
and other creative content. They are based on the diffusion process, which is a way of creating new images by gradually adding noise to an existing image. This specific type of diffusion model was proposed in High-Resolution Image Synthesis with Latent Diffusion Models by Robin Rombach, Andreas...
each layer’s data capacity is progressive reduced. This forces the network to learn only the most important patterns hidden within the input data—calledlatent variables, or thelatent space—so that the decoder network can accurately reconstruct the original input despite now having less information...
In December 2021, a papertitled, ‘High-Resolution Image Synthesis with Latent Diffusion Models’ introduced latent diffusion models. These models used an autoencoder to compress the images into a comparatively smaller latent space during training. Then, the autoencoder is used to decompress the fina...
algorithm rewards neural network configurations with a lower loss function since they're more similar, while a higher loss function is penalized. This training process lets the autoencoder capture the underlying structure of and latent variables in the training data and model it into the neural ...
Below is a breakdown: Diffusion models:Also known as denoising diffusion probabilistic models (DDPMs), diffusion models are generative models that determine vectors in latent space through a two-step process during training. The two steps are forward diffusion and reverse diffusion. The forward diffus...
Google’s Imagen Video is a text-conditional video generation system based on a cascade of video diffusion models. Given a text prompt, Imagen Video generates high-definition videos using a base video generation model and a sequence of interleaved spatial and temporal video super-resolution models....