From the 1 of 6 linked papers with an AI index.
6 papers
On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting
In-Hwan Jin, Hyeongju Mun, Joonsoo Kim +2
The paper proposes two mixture‑of‑experts frameworks for dynamic 3D Gaussian splatting that combine multiple specialized deformation models to improve robustness in dynamic scene r…
LivingWorld: Interactive 4D World Generation with Environmental Dynamics
Hyeongju Mun, In-Hwan Jin, Sohyeong Kim +1
We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances in 3D scene generation enable lar…
HOIGS: Human-Object Interaction Gaussian Splatting
Taewoo Kim, Suwoong Yeom, Jaehyun Pyun +6
Reconstructing dynamic scenes with complex human-object interactions is a fundamental challenge in computer vision and graphics. Existing Gaussian Splatting methods either rely on…
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…
MoE-GS: Mixture of Experts for Dynamic Gaussian Splatting
In-Hwan Jin, Hyeongju Mun, Joonsoo Kim +2
Recent advances in dynamic scene reconstruction have significantly benefited from 3D Gaussian Splatting, yet existing methods show inconsistent performance across diverse scenes, i…
Optimizing 4D Gaussians for Dynamic Scene Video from Single Landscape Images
In-Hwan Jin, Haesoo Choo, Seong-Hun Jeong +4
To achieve realistic immersion in landscape images, fluids such as water and clouds need to move within the image while revealing new scenes from various camera perspectives. Recen…