1 citations · 4 across the 12 of their papers we have counts for
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Patch-to-Global: Random Patch Diffusion for Globally Consistent Megapixel Artifact Inpainting in Whole Slide Images
Hyeseong Lee, Eunsu Kim, D M Bappy +6
Although deep learning has advanced Whole Slide Image (WSI) Analysis, tissue artifacts like bubbles and folds often cause silent failures by concealing essential morphology. Curren…
PersonaCraft: Personalized and Controllable Full-Body Multi-Human Scene Generation Using Occlusion-Aware 3D-Conditioned Diffusion
Gwanghyun Kim, Suh Yoon Jeon, Seunggyu Lee +1
We present PersonaCraft, a framework for controllable and occlusion-robust full-body personalized image synthesis of multiple individuals in complex scenes. Current methods struggl…
Contribution-based Low-Rank Adaptation with Pre-training Model for Real Image Restoration
Donwon Park, Hayeon Kim, Se Young Chun
Recently, pre-trained model and efficient parameter tuning have achieved remarkable success in natural language processing and high-level computer vision with the aid of masked mod…
On Exact Inversion of DPM-Solvers
Seongmin Hong, Kyeonghyun Lee, Suh Yoon Jeon +2
Diffusion probabilistic models (DPMs) are a key component in modern generative models. DPM-solvers have achieved reduced latency and enhanced quality significantly, but have posed…
Fully Quantized Always-on Face Detector Considering Mobile Image Sensors
Haechang Lee, Wongi Jeong, Dongil Ryu +4
Despite significant research on lightweight deep neural networks (DNNs) designed for edge devices, the current face detectors do not fully meet the requirements for "intelligent" C…
PODIA-3D: Domain Adaptation of 3D Generative Model Across Large Domain Gap Using Pose-Preserved Text-to-Image Diffusion
Gwanghyun Kim, Ji Ha Jang, Se Young Chun
Recently, significant advancements have been made in 3D generative models, however training these models across diverse domains is challenging and requires an huge amount of traini…
On the Robustness of Normalizing Flows for Inverse Problems in Imaging
Seongmin Hong, Inbum Park, Se Young Chun
Conditional normalizing flows can generate diverse image samples for solving inverse problems. Most normalizing flows for inverse problems in imaging employ the conditional affine…
DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Model
Gwanghyun Kim, Se Young Chun
Recent 3D generative models have achieved remarkable performance in synthesizing high resolution photorealistic images with view consistency and detailed 3D shapes, but training th…