6 papers · 1 filter
Hand-4DGS: Feed-Forward 3D Gaussian Splatting for 4D Hand Reconstruction from Egocentric Videos
Jeongmin Bae, Seoha Kim, Marc Pollefeys +3
Dynamic 3D hand reconstruction from egocentric videos is essential for next-generation computing platforms such as AR/VR and AI glasses. Despite its importance, most prior works fo…
Compensating Spatiotemporally Inconsistent Observations for Online Dynamic 3D Gaussian Splatting
Youngsik Yun, Jeongmin Bae, Hyunseung Son +4
Online reconstruction of dynamic scenes is significant as it enables learning scenes from live-streaming video inputs, while existing offline dynamic reconstruction methods rely on…
4D Scaffold Gaussian Splatting with Dynamic-Aware Anchor Growing for Efficient and High-Fidelity Dynamic Scene Reconstruction
Woong Oh Cho, In Cho, Seoha Kim +3
Modeling dynamic scenes through 4D Gaussians offers high visual fidelity and fast rendering speeds, but comes with significant storage overhead. Recent approaches mitigate this cos…
Rethinking Open-Vocabulary Segmentation of Radiance Fields in 3D Space
Hyunjee Lee, Youngsik Yun, Jeongmin Bae +2
Understanding the 3D semantics of a scene is a fundamental problem for various scenarios such as embodied agents. While NeRFs and 3DGS excel at novel-view synthesis, previous metho…
Per-Gaussian Embedding-Based Deformation for Deformable 3D Gaussian Splatting
Jeongmin Bae, Seoha Kim, Youngsik Yun +3
As 3D Gaussian Splatting (3DGS) provides fast and high-quality novel view synthesis, it is a natural extension to deform a canonical 3DGS to multiple frames for representing a dyna…
Sync-NeRF: Generalizing Dynamic NeRFs to Unsynchronized Videos
Seoha Kim, Jeongmin Bae, Youngsik Yun +3
Recent advancements in 4D scene reconstruction using neural radiance fields (NeRF) have demonstrated the ability to represent dynamic scenes from multi-view videos. However, they f…