Kyungmin Jo — accepted AI-conference papers

2025

Devil is in the Detail: Towards Injecting Fine Details of Image Prompt in Image Generation via Conflict-free Guidance and Stratified Attention

CVPR 2025poster

While large-scale text-to-image diffusion models enable the generation of high-quality, diverse images from text prompts, these prompts struggle to capture intricate details, such as textures, preventing the user intent from being reflected. This limitation has led to efforts to generate images cond…

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2023

3D-Aware Generative Model for Improved Side-View Image Synthesis

Kyungmin Jo, Wonjoon Jin, Jaegul Choo, Hyunjoon Lee, Sunghyun Cho

ICCV 2023poster

While recent 3D-aware generative models have shown photo-realistic image synthesis with multi-view consistency, the synthesized image quality degrades depending on the camera pose (e.g., a face with a blurry and noisy boundary at a side viewpoint). Such degradation is mainly caused by the difficulty…

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2023

Perspective Projection-Based 3d CT Reconstruction from Biplanar X-Rays

Daeun Kyung, Kyungmin Jo, Jaegul Choo, Joonseok Lee, Edward Choi

ICASSP 2023accepted

X-ray computed tomography (CT) is one of the most common imaging techniques used to diagnose various diseases in the medical field. Its high contrast sensitivity and spatial resolution allow the physician to observe details of body parts such as bones, soft tissue, blood vessels, etc. As it involves…

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