3 citations · 5 across the 10 of their papers we have counts for
10 papers
PLATYPUS: Progressive Local Surface Estimator for Arbitrary-Scale Point Cloud Upsampling
Donghyun Kim, Hyeonkyeong Kwon, Yumin Kim +1
3D point clouds are increasingly vital for applications like autonomous driving and robotics, yet the raw data captured by sensors often suffer from noise and sparsity, creating ch…
Disentangling Disentangled Representations: Towards Improved Latent Units via Diffusion Models
Youngjun Jun, Jiwoo Park, Kyobin Choo +2
Disentangled representation learning (DRL) aims to break down observed data into core intrinsic factors for a profound understanding of the data. In real-world scenarios, manually…
Parameter Efficient Fine Tuning for Multi-scanner PET to PET Reconstruction
Yumin Kim, Gayoon Choi, Seong Jae Hwang
Reducing scan time in Positron Emission Tomography (PET) imaging while maintaining high-quality images is crucial for minimizing patient discomfort and radiation exposure. Due to t…
Slice-Consistent 3D Volumetric Brain CT-to-MRI Translation with 2D Brownian Bridge Diffusion Model
Kyobin Choo, Youngjun Jun, Mijin Yun +1
In neuroimaging, generally, brain CT is more cost-effective and accessible imaging option compared to MRI. Nevertheless, CT exhibits inferior soft-tissue contrast and higher noise…
FALCON: Frequency Adjoint Link with CONtinuous Density Mask for Fast Single Image Dehazing
Donghyun Kim, Seil Kang, Seong Jae Hwang
Image dehazing, addressing atmospheric interference like fog and haze, remains a pervasive challenge crucial for robust vision applications such as surveillance and remote sensing…
EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation
Chanyoung Kim, Woojung Han, Dayun Ju +1
Semantic segmentation has innately relied on extensive pixel-level annotated data, leading to the emergence of unsupervised methodologies. Among them, leveraging self-supervised Vi…