5 papers
Spectrally-Guided Diffusion Noise Schedules
Carlos Esteves, Ameesh Makadia
Denoising diffusion models are widely used for high-quality image and video generation. Their performance depends on noise schedules, which define the distribution of noise levels…
Decomposing Private Image Generation via Coarse-to-Fine Wavelet Modeling
Jasmine Bayrooti, Weiwei Kong, Natalia Ponomareva +3
Generative models trained on sensitive image datasets risk memorizing and reproducing individual training examples, making strong privacy guarantees essential. While differential p…
Spectral Image Tokenizer
Carlos Esteves, Mohammed Suhail, Ameesh Makadia
Image tokenizers map images to sequences of discrete tokens, and are a crucial component of autoregressive transformer-based image generation. The tokens are typically associated w…
Factorized Video Autoencoders for Efficient Generative Modelling
Mohammed Suhail, Carlos Esteves, Leonid Sigal +1
Latent variable generative models have emerged as powerful tools for generative tasks including image and video synthesis. These models are enabled by pretrained autoencoders that…
Single Mesh Diffusion Models with Field Latents for Texture Generation
Thomas W. Mitchel, Carlos Esteves, Ameesh Makadia
We introduce a framework for intrinsic latent diffusion models operating directly on the surfaces of 3D shapes, with the goal of synthesizing high-quality textures. Our approach is…