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The Latent Diffusion Model (LDM) [1] is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) [2] group at LMU Munich. [ 3 ] Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian ) on training images.
High-Resolution Image Synthesis with Latent Diffusion Models (2021, updated in 2022). [80] This paper describes the latent diffusion model (LDM). This is the backbone of the Stable Diffusion architecture. Classifier-Free Diffusion Guidance (2022). [29]
Diffusion models themselves can be used to perform upscaling. Cascading diffusion model stacks multiple diffusion models one after another, in the style of Progressive GAN. The lowest level is a standard diffusion model that generate 32x32 image, then the image would be upscaled by a diffusion model specifically trained for upscaling, and the ...
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
The Bridge of Time to the Lost City facing Sun central mall. Sun City is a luxury resort and casino, situated in the North West Province of South Africa.It is located between the Elands River and the Pilanesberg, built on the land of Bakubung Village (known as Ledig) about 140 km (90 miles) northwest of Johannesburg, near the city of Rustenburg.
Applications based on diffusion maps include face recognition, [7] spectral clustering, low dimensional representation of images, image segmentation, [8] 3D model segmentation, [9] speaker verification [10] and identification, [11] sampling on manifolds, anomaly detection, [12] [13] image inpainting, [14] revealing brain resting state networks ...
Segmentation of a 512 × 512 image takes less than a second on a modern (2015) GPU using the U-Net architecture. [1] [3] [4] [5] The U-Net architecture has also been employed in diffusion models for iterative image denoising. [6] This technology underlies many modern image generation models, such as DALL-E, Midjourney, and Stable Diffusion.
A neural radiance field (NeRF) is a method based on deep learning for reconstructing a three-dimensional representation of a scene from two-dimensional images. The NeRF model enables downstream applications of novel view synthesis, scene geometry reconstruction, and obtaining the reflectance properties of the scene. Additional scene properties ...