title: Revising Densification in Gaussian Splatting
summary: In this paper, we address the limitations of Adaptive Density Control (ADC)
  in 3D Gaussian Splatting (3DGS), a scene representation method achieving
  high-quality, photorealistic results for novel view synthesis. ADC has been
  introduced for automatic 3D point primitive management, controlling
  densification and pruning, however, with certain limitations in the
  densification logic. Our main contribution is a more principled, pixel-error
  driven formulation for density control in 3DGS, leveraging an auxiliary,
  per-pixel error function as the criterion for densification. We further
  introduce a mechanism to control the total number of primitives generated per
  scene and correct a bias in the current opacity handling strategy of ADC during
  cloning operations. Our approach leads to consistent quality improvements
  across a variety of benchmark scenes, without sacrificing the method's
  efficiency.
paper_authors._id: 66160fde1ddd756333ba96c4
paper_authors.name: Samuel Rota Bulò
paper_authors._id: 66160fde1ddd756333ba96c5
paper_authors.name: Lorenzo Porzi
paper_authors._id: 66160fde1ddd756333ba96c6
paper_authors.name: Peter Kontschieder
paper_title: Revising Densification in Gaussian Splatting
paper_summary: In this paper, we address the limitations of Adaptive Density Control (ADC)
  in 3D Gaussian Splatting (3DGS), a scene representation method achieving
  high-quality, photorealistic results for novel view synthesis. ADC has been
  introduced for automatic 3D point primitive management, controlling
  densification and pruning, however, with certain limitations in the
  densification logic. Our main contribution is a more principled, pixel-error
  driven formulation for density control in 3DGS, leveraging an auxiliary,
  per-pixel error function as the criterion for densification. We further
  introduce a mechanism to control the total number of primitives generated per
  scene and correct a bias in the current opacity handling strategy of ADC during
  cloning operations. Our approach leads to consistent quality improvements
  across a variety of benchmark scenes, without sacrificing the method's
  efficiency.
paper_ai_summary: A new pixel-error driven formulation for density control in 3D Gaussian Splatting improves consistency without sacrificing efficiency.
paper_ai_keywords: Adaptive Density Control 3D Gaussian Splatting pixel-error driven formulation density control per-pixel error function opacity handling strategy