mlsanityData to 7 Oct 2026

Gradient-Direction-Aware Density Control for 3D Gaussian Splatting

arXiv 2508.09239 ↗First posted 12 Aug 2025cs.CV cs.AIcited by 7

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Abstract (arXiv)

The emergence of 3D Gaussian Splatting (3DGS) has significantly advanced Novel View Synthesis (NVS) through explicit scene representation, enabling real-time photorealistic rendering. However, existing approaches manifest two critical limitations in complex scenarios: (1) Over-reconstruction occurs when persistent large Gaussians cannot meet adaptive splitting thresholds during density control. This is exacerbated by conflicting gradient directions that prevent effective splitting of these Gaussians; (2) Over-densification of Gaussians occurs in regions with aligned gradient aggregation, leading to redundant component proliferation. This redundancy significantly increases memory overhead due to unnecessary data retention. We present Gradient-Direction-Aware Gaussian Splatting (GDAGS) to address these challenges. Our key innovations: the Gradient Coherence Ratio (GCR), computed through normalized gradient vector norms, which explicitly discriminates Gaussians with concordant versus conflicting gradient directions; and a nonlinear dynamic weighting mechanism leverages the GCR to enable gradient-direction-aware density control. Specifically, GDAGS prioritizes conflicting-gradient Gaussians during splitting operations to enhance geometric details while suppressing redundant concordant-direction Gaussians. Conversely, in cloning processes, GDAGS promotes concordant-direction Gaussian densification for structural completion while preventing conflicting-direction Gaussian overpopulation. Comprehensive evaluations across diverse real-world benchmarks demonstrate that GDAGS achieves superior rendering quality while effectively mitigating over-reconstruction, suppressing over-densification, and constructing compact scene representations.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 26 of its 35 references that are in the map. First posted on arXiv 12 Aug 2025.

Builds on

26 of 35 references.

References · 26

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  3. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  4. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  5. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  6. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,607
  7. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
  8. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
  9. 2023Mip-Splatting: Alias-free 3D Gaussian Splattingcited by 661
  10. 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 569
  11. 2023Compact 3D Gaussian Representation for Radiance Fieldcited by 365
  12. 2024Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenescited by 226
14 more
  1. 20243D Gaussian Splatting as Markov Chain Monte Carlocited by 210
  2. 2024Mini-Splatting: Representing Scenes with a Constrained Number of Gaussianscited by 208
  3. 2024GaussianPro: 3D Gaussian Splatting with Progressive Propagationcited by 199
  4. 2024Taming 3DGS: High-Quality Radiance Fields with Limited Resourcescited by 198
  5. 2024Pixel-GS: Density Control with Pixel-aware Gradient for 3D Gaussian Splattingcited by 111
  6. 2024RaDe-GS: Rasterizing Depth in Gaussian Splattingcited by 110
  7. 2024FreGS: 3D Gaussian Splatting with Progressive Frequency Regularizationcited by 103
  8. 2024GES: Generalized Exponential Splatting for Efficient Radiance Field Renderingcited by 92
  9. 2024AbsGS: Recovering Fine Details for 3D Gaussian Splattingcited by 80
  10. 20243D-HGS: 3D Half-Gaussian Splattingcited by 43
  11. 2025Frequency-Aware Density Control via Reparameterization for High-Quality Rendering of 3D Gaussian Splattingcited by 8
  12. 2025HoGS: Unified Near and Far Object Reconstruction via Homogeneous Gaussian Splattingcited by 4
  13. 2025Decomposing Densification in Gaussian Splatting for Faster 3D Scene Reconstructioncited by 3
  14. 2025PSRGS:Progressive Spectral Residual of 3D Gaussian for High-Frequency Recoverycited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 5.

7 papers.