2 citations · 5 across the 25 of their papers we have counts for
5 papers · 2 filters
HarmonyView: Harmonizing Consistency and Diversity in One-Image-to-3D
Sangmin Woo, Byeongjun Park, Hyojun Go +2
Recent progress in single-image 3D generation highlights the importance of multi-view coherency, leveraging 3D priors from large-scale diffusion models pretrained on Internet-scale…
Denoising Task Routing for Diffusion Models
Byeongjun Park, Sangmin Woo, Hyojun Go +2
Diffusion models generate highly realistic images by learning a multi-step denoising process, naturally embodying the principles of multi-task learning (MTL). Despite the inherent…
Multi-Architecture Multi-Expert Diffusion Models
Yunsung Lee, Jin-Young Kim, Hyojun Go +3
In this paper, we address the performance degradation of efficient diffusion models by introducing Multi-architecturE Multi-Expert diffusion models (MEME). We identify the need for…
ScoreCL: Augmentation-Adaptive Contrastive Learning via Score-Matching Function
Jin-Young Kim, Soonwoo Kwon, Hyojun Go +3
Self-supervised contrastive learning (CL) has achieved state-of-the-art performance in representation learning by minimizing the distance between positive pairs while maximizing th…
Addressing Negative Transfer in Diffusion Models
Hyojun Go, JinYoung Kim, Yunsung Lee +4
Diffusion-based generative models have achieved remarkable success in various domains. It trains a shared model on denoising tasks that encompass different noise levels simultaneou…