28 citations · 80 across the 9 of their papers we have counts for
4 papers · 1 filter
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong +2
Denoising diffusion probabilistic models (DDPM) have shown remarkable performance in unconditional image generation. However, due to the stochasticity of the generative process in…
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection
Yonghyun Jeong, Doyeon Kim, Seungjai Min +3
The advancement in numerous generative models has a two-fold effect: a simple and easy generation of realistic synthesized images, but also an increased risk of malicious abuse of…
Adversarial Learning of Semantic Relevance in Text to Image Synthesis
Miriam Cha, Youngjune L. Gwon, H. T. Kung
We describe a new approach that improves the training of generative adversarial nets (GANs) for synthesizing diverse images from a text input. Our approach is based on the conditio…
Adversarial nets with perceptual losses for text-to-image synthesis
Miriam Cha, Youngjune Gwon, H. T. Kung
Recent approaches in generative adversarial networks (GANs) can automatically synthesize realistic images from descriptive text. Despite the overall fair quality, the generated ima…