Feature-Based Metrics for Exploring the Latent Space of Generative Models

By Samuli Laine. 2018

47 citations recorded by the source corpus.

Subfields: Generative Models

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Generative Models

1. Bolei Zhou
2. Yujun Shen
3. Daniel Cohen-Or
4. Eli Shechtman
5. Jun-Yan Zhu
6. Dani Lischinski
7. Richard Zhang
8. Or Patashnik

Citations in the corpus

• A Style-Based Generator Architecture for Generative Adversarial Networks (2018, background): “The properties of the latent space are also poorly understood, and the commonly demonstrated latent space interpolations [12, 48, 34] provide no quantitative way to compare different generators against each other.”
• Interpreting the Latent Space of GANs for Semantic Face Editing (2019, background): “Prior work focused on exploring how to make the output image vary smoothly from one synthesis to another through interpolation in the latent space, regardless of whether the image is semantically controllable [22, 29].”