no code implementations • 17 Oct 2023 • Gyuseong Lee, Wooseok Jang, Jin Hyeon Kim, Jaewoo Jung, Seungryong Kim
By using both PEFT and MoA methods, we effectively alleviate the performance deterioration caused by distribution shifts and achieve state-of-the-art performance on diverse DG benchmarks.
no code implementations • 5 Jun 2023 • Sunwoo Kim, Wooseok Jang, Hyunsu Kim, Junho Kim, Yunjey Choi, Seungryong Kim, Gayeong Lee
From the users' standpoint, prompt engineering is a labor-intensive process, and users prefer to provide a target word for editing instead of a full sentence.
1 code implementation • 14 Mar 2023 • Junyoung Seo, Wooseok Jang, Min-Seop Kwak, Jaehoon Ko, Hyeonsu Kim, Junho Kim, Jin-Hwa Kim, Jiyoung Lee, Seungryong Kim
Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural radiance field (NeRF) in the zero-shot setting.
no code implementations • 17 Dec 2022 • Gyeongnyeon Kim, Wooseok Jang, Gyuseong Lee, Susung Hong, Junyoung Seo, Seungryong Kim
Generative models have recently undergone significant advancement due to the diffusion models.
4 code implementations • ICCV 2023 • Susung Hong, Gyuseong Lee, Wooseok Jang, Seungryong Kim
Denoising diffusion models (DDMs) have attracted attention for their exceptional generation quality and diversity.