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Found 4 papers, 1 papers with code
Analysis of Classifier-Free Guidance Weight Schedulers
Classifier-Free Guidance (CFG) enhances the quality and condition adherence of text-to-image diffusion models.
LED: Latent Variable-based Estimation of Density
Modern generative models are roughly divided into two main categories: (1) models that can produce high-quality random samples, but cannot estimate the exact density of new data points and (2) those that provide exact density estimation, at the expense of sample quality and compactness of the latent space.
Cross-modal Deep Face Normals with Deactivable Skip Connections
Core to our approach is a novel module that we call deactivable skip connections, which allows integrating both the auto-encoded and image-to-normal branches within the same architecture that can be trained end-to-end.
A Decoupled 3D Facial Shape Model by Adversarial Training
Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations.
