226 citations · 454 across the 13 of their papers we have counts for
28 papers
Diffusion Guided Domain Adaptation of Image Generators
Kunpeng Song, Ligong Han, Bingchen Liu +2
Can a text-to-image diffusion model be used as a training objective for adapting a GAN generator to another domain? In this paper, we show that the classifier-free guidance can be…
Formal Analysis of Art: Proxy Learning of Visual Concepts from Style Through Language Models
Diana Kim, Ahmed Elgammal, Marian Mazzone
We present a machine learning system that can quantify fine art paintings with a set of visual elements and principles of art. This formal analysis is fundamental for understanding…
Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis
Bingchen Liu, Yizhe Zhu, Kunpeng Song +1
Training Generative Adversarial Networks (GAN) on high-fidelity images usually requires large-scale GPU-clusters and a vast number of training images. In this paper, we study the f…
Self-Supervised Sketch-to-Image Synthesis
Bingchen Liu, Yizhe Zhu, Kunpeng Song +1
Imagining a colored realistic image from an arbitrarily drawn sketch is one of the human capabilities that we eager machines to mimic. Unlike previous methods that either requires…
Spatial Frequency Bias in Convolutional Generative Adversarial Networks
Mahyar Khayatkhoei, Ahmed Elgammal
As the success of Generative Adversarial Networks (GANs) on natural images quickly propels them into various real-life applications across different domains, it becomes more and mo…
TIME: Text and Image Mutual-Translation Adversarial Networks
Bingchen Liu, Kunpeng Song, Yizhe Zhu +2
Focusing on text-to-image (T2I) generation, we propose Text and Image Mutual-Translation Adversarial Networks (TIME), a lightweight but effective model that jointly learns a T2I ge…