3 citations · 3 across the 4 of their papers we have counts for
6 papers
Articulated Object Reconstruction from Rest-State Observation
Daeun Lee, Jaeah Lee, Woosung Kim +2
Building interactive digital twins requires recovering both 3D geometry and the kinematic structures that govern how objects articulate. Yet existing methods for articulated object…
TRiGS: Temporal Rigid-Body Motion for Scalable 4D Gaussian Splatting
Suwoong Yeom, Joonsik Nam, Seunggyu Choi +7
Recent 4D Gaussian Splatting (4DGS) methods achieve impressive dynamic scene reconstruction but often rely on piecewise linear velocity approximations and short temporal windows. T…
Extend3D: Town-Scale 3D Generation
Seungwoo Yoon, Jinmo Kim, Jaesik Park
In this paper, we propose Extend3D, a training-free pipeline for 3D scene generation from a single image, built upon an object-centric 3D generative model. To overcome the limitati…
Metropolis-Hastings Sampling for 3D Gaussian Reconstruction
Hyunjin Kim, Haebeom Jung, Jaesik Park
We propose an adaptive sampling framework for 3D Gaussian Splatting (3DGS) that leverages comprehensive multi-view photometric error signals within a unified Metropolis-Hastings ap…
Targetless LiDAR-Camera Calibration with Neural Gaussian Splatting
Haebeom Jung, Namtae Kim, Jungwoo Kim +1
Accurate LiDAR-camera calibration is crucial for multi-sensor systems. However, traditional methods often rely on physical targets, which are impractical for real-world deployment.…
Deep Cost Ray Fusion for Sparse Depth Video Completion
Jungeon Kim, Soongjin Kim, Jaesik Park +1
In this paper, we present a learning-based framework for sparse depth video completion. Given a sparse depth map and a color image at a certain viewpoint, our approach makes a cost…