Generating Large Images from Latent Vectors

By David R Ha. 2016

23 citations recorded by the source corpus.

How researchers see this paper

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

1. Luca Melis
2. Jamie Hayes
3. Anh Totti Nguyen
4. Congzheng Song
5. Emiliano De Cristofaro
6. George Danezis
7. Nader Akoury
8. Nicholas Carlini

Citations in the corpus

• How to Represent Part-Whole Hierarchies in a Neural Network (2021, methodology): “This is called a neural field,14 and this way of using neural networks has recently become very popular (Ha, 2016; Sitzmann et al., 2020; Mildenhall et al., 2020).”
• LOGAN: Membership Inference Attacks Against Generative Models (2017, background): “It has also been shown that combining the DCGAN architecture with a VAE yields more realistic generated samples [45].”
• Spatial PixelCNN: Generating Images from Patches (2017, methodology): “Our framework most closely resembles Ha, 2016, which combines spatial coordinates, and the latent code from a VAE, trained as a GAN end-to-end on full-sized images.”