18 citations · 38 across the 5 of their papers we have counts for
7 papers · 1 filter
FlashDecoder: Real-Time Latent-to-Pixel Streaming Decoder with Transformers
Minguk Kang, Suha Kwak
Real-time video generation demands fast decoding as much as fast denoising, yet current latent video diffusion models rely on 3D convolutional decoders that are slow and memory-int…
Distilling Diffusion Models into Conditional GANs
Minguk Kang, Richard Zhang, Connelly Barnes +6
We propose a method to distill a complex multistep diffusion model into a single-step conditional GAN student model, dramatically accelerating inference, while preserving image qua…
Holistic Evaluation of Text-To-Image Models
Tony Lee, Michihiro Yasunaga, Chenlin Meng +15
The stunning qualitative improvement of recent text-to-image models has led to their widespread attention and adoption. However, we lack a comprehensive quantitative understanding…
Fill-Up: Balancing Long-Tailed Data with Generative Models
Joonghyuk Shin, Minguk Kang, Jaesik Park
Modern text-to-image synthesis models have achieved an exceptional level of photorealism, generating high-quality images from arbitrary text descriptions. In light of the impressiv…
Extending CLIP's Image-Text Alignment to Referring Image Segmentation
Seoyeon Kim, Minguk Kang, Dongwon Kim +2
Referring Image Segmentation (RIS) is a cross-modal task that aims to segment an instance described by a natural language expression. Recent methods leverage large-scale pretrained…
Scaling up GANs for Text-to-Image Synthesis
Minguk Kang, Jun-Yan Zhu, Richard Zhang +4
The recent success of text-to-image synthesis has taken the world by storm and captured the general public's imagination. From a technical standpoint, it also marked a drastic chan…