activity
20202022
most citedTowards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis

109 citations · 122 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV202212 cited

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…

cs.CV2021109 cited

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…

cs.CV20201 cited

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…

cs.CV2020

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…

cs.CV2020

Sketch-to-Art: Synthesizing Stylized Art Images From Sketches

Bingchen Liu, Kunpeng Song, Ahmed Elgammal

We propose a new approach for synthesizing fully detailed art-stylized images from sketches. Given a sketch, with no semantic tagging, and a reference image of a specific style, th…