Liquid Neural Networks as a Drop-in Continuous-Time Deformation Field for Dynamic 3D Gaussian Splatting
Researchers propose replacing the MLP-based deformation field in Deformable 3D Gaussian Splatting with Liquid Neural Networks (LNNs), enabling truly continuous-time modeling of dynamic 3D scenes. The approach achieves performance parity or better than baseline methods while providing mathematically principled temporal smoothness, particularly excelling on scenes with complex articulated motion.