3 papers
cs.CV2026
CausalGS: Learning Physical Causality of 3D Dynamic Scenes with Gaussian Representations
Nengbo Lu, Minghua Pan
Learning a physical model from video data that can comprehend physical laws and predict the future trajectories of objects is a formidable challenge in artificial intelligence. Pri…
cs.CV2026
VeloGauss: Learning Physically Consistent Gaussian Velocity Fields from Videos
Nengbo Lu, Bin Zhao
In this paper, we aim to jointly model the geometry, appearance, and physical information of 3D scenes solely from dynamic multi-view videos, without relying on any physical priors…
cs.CV2026
GS-DMSR: Dynamic Sensitive Multi-scale Manifold Enhancement for Accelerated High-Quality 3D Gaussian Splatting
Nengbo Lu, Minghua Pan, Shaohua Sun +1
In the field of 3D dynamic scene reconstruction, how to balance model convergence rate and rendering quality has long been a critical challenge that urgently needs to be addressed,…