Search Results for author: Wooseok Jang

Found 5 papers, 2 papers with code

Domain Generalization Using Large Pretrained Models with Mixture-of-Adapters

no code implementations17 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.

Domain Generalization

User-friendly Image Editing with Minimal Text Input: Leveraging Captioning and Injection Techniques

no code implementations5 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.

Prompt Engineering

Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

1 code implementation14 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.

Single-View 3D Reconstruction Text to 3D

Improving Sample Quality of Diffusion Models Using Self-Attention Guidance

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.

Denoising Image Generation

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