SCas4D: Structural Cascaded Optimization for Boosting Persistent 4D
  Novel View Synthesis
Persistent dynamic scene modeling for tracking and novel-view synthesis
remains challenging due to the difficulty of capturing accurate deformations
while maintaining computational efficiency. We propose SCas4D, a cascaded
optimization framework that leverages structural patterns in 3D Gaussian
Splatting for dynamic scenes. The key idea is that real-world deformations
often exhibit hierarchical patterns, where groups of Gaussians share similar
transformations. By progressively refining deformations from coarse part-level
to fine point-level, SCas4D achieves convergence within 100 iterations per time
frame and produces results comparable to existing methods with only
one-twentieth of the training iterations. The approach also demonstrates
effectiveness in self-supervised articulated object segmentation, novel view
synthesis, and dense point tracking tasks.
68f1e5d66e0bef323a690014
Jipeng Lyu
68f1e5d66e0bef323a690015
Jiahua Dong
68f1e5d66e0bef323a690016
Yu-Xiong Wang
SCas4D: Structural Cascaded Optimization for Boosting Persistent 4D
  Novel View Synthesis
Persistent dynamic scene modeling for tracking and novel-view synthesis
remains challenging due to the difficulty of capturing accurate deformations
while maintaining computational efficiency. We propose SCas4D, a cascaded
optimization framework that leverages structural patterns in 3D Gaussian
Splatting for dynamic scenes. The key idea is that real-world deformations
often exhibit hierarchical patterns, where groups of Gaussians share similar
transformations. By progressively refining deformations from coarse part-level
to fine point-level, SCas4D achieves convergence within 100 iterations per time
frame and produces results comparable to existing methods with only
one-twentieth of the training iterations. The approach also demonstrates
effectiveness in self-supervised articulated object segmentation, novel view
synthesis, and dense point tracking tasks.
SCas4D, a cascaded optimization framework using 3D Gaussian Splatting, efficiently models dynamic scenes by leveraging hierarchical deformation patterns, enabling fast convergence and high-quality results in various tasks.
3D Gaussian Splatting cascaded optimization framework hierarchical patterns deformations self-supervised articulated object segmentation novel view synthesis dense point tracking