5 papers · 1 filter
GLINT: Modeling Scene-Scale Transparency via Gaussian Radiance Transport
Youngju Na, Jaeseong Yun, Soohyun Ryu +3
While 3D Gaussian splatting has emerged as a powerful paradigm, it fundamentally fails to model transparency such as glass panels. The core challenge lies in decoupling the intertw…
MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos
Taeyeon Kim, Youngju Na, Jumin Lee +3
Transferring articulated motion from monocular videos to rigged 3D characters is challenging due to pose ambiguity in 2D observations and morphological differences between source a…
AegisRF: Adversarial Perturbations Guided with Sensitivity for Protecting Intellectual Property of Neural Radiance Fields
Woo Jae Kim, Kyu Beom Han, Yoonki Cho +4
As Neural Radiance Fields (NeRFs) have emerged as a powerful tool for 3D scene representation and novel view synthesis, protecting their intellectual property (IP) from unauthorize…
Pose-free 3D Gaussian splatting via shape-ray estimation
Youngju Na, Taeyeon Kim, Jumin Lee +3
While generalizable 3D Gaussian splatting enables efficient, high-quality rendering of unseen scenes, it heavily depends on precise camera poses for accurate geometry. In real-worl…
UFORecon: Generalizable Sparse-View Surface Reconstruction from Arbitrary and UnFavOrable Sets
Youngju Na, Woo Jae Kim, Kyu Beom Han +2
Generalizable neural implicit surface reconstruction aims to obtain an accurate underlying geometry given a limited number of multi-view images from unseen scenes. However, existin…