mlsanityData to 14 Oct 2026

1000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering

arXiv 2503.16422 ↗First posted 20 Mar 2025cs.CVcited by 13

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Abstract (arXiv)

4D Gaussian Splatting (4DGS) has recently gained considerable attention as a method for reconstructing dynamic scenes. Despite achieving superior quality, 4DGS typically requires substantial storage and suffers from slow rendering speed. In this work, we delve into these issues and identify two key sources of temporal redundancy. (Q1) Short-Lifespan Gaussians: 4DGS uses a large portion of Gaussians with short temporal span to represent scene dynamics, leading to an excessive number of Gaussians. (Q2) Inactive Gaussians: When rendering, only a small subset of Gaussians contributes to each frame. Despite this, all Gaussians are processed during rasterization, resulting in redundant computation overhead. To address these redundancies, we present 4DGS-1K, which runs at over 1000 FPS on modern GPUs. For Q1, we introduce the Spatial-Temporal Variation Score, a new pruning criterion that effectively removes short-lifespan Gaussians while encouraging 4DGS to capture scene dynamics using Gaussians with longer temporal spans. For Q2, we store a mask for active Gaussians across consecutive frames, significantly reducing redundant computations in rendering. Compared to vanilla 4DGS, our method achieves a 41× reduction in storage and 9× faster rasterization speed on complex dynamic scenes, while maintaining comparable visual quality. Please see our project page at https://4DGS-1K.github.io.

Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). Builds on 43 of its 50 references that are in the map. First posted on arXiv 20 Mar 2025.

Builds on

43 of 50 references.

References · 43

  1. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,177
  3. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  4. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  5. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  6. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,465
  7. 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
  8. 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,157
  9. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 964
  10. 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 759
  11. 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
  12. 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 737
31 more
  1. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 673
  2. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  3. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
  4. 2023Real-time Photorealistic Dynamic Scene Representation and Rendering with 4D Gaussian Splattingcited by 476
  5. 2023LightGaussian: Unbounded 3D Gaussian Compression with 15x Reduction and 200+ FPScited by 436
  6. 2023Compact 3D Gaussian Representation for Radiance Fieldcited by 372
  7. 2023SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenescited by 347
  8. 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 346
  9. 2023Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesiscited by 344
  10. 2024Mini-Splatting: Representing Scenes with a Constrained Number of Gaussianscited by 213
  11. 20244D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenescited by 189
  12. 2023HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Samplingcited by 174
  13. 2022Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-timecited by 165
  14. 2022NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fieldscited by 152
  15. 2022VoxGRAF: Fast 3D-Aware Image Synthesis with Sparse Voxel Gridscited by 133
  16. 2024Reducing the Memory Footprint of 3D Gaussian Splattingcited by 133
  17. 2023CompGS: Smaller and Faster Gaussian Splatting with Vector Quantizationcited by 130
  18. 2022Mixed Neural Voxels for Fast Multi-view Video Synthesiscited by 127
  19. 2022Streaming Radiance Fields for 3D Video Synthesiscited by 119
  20. 2024RadSplat: Radiance Field-Informed Gaussian Splatting for Robust Real-Time Rendering with 900+ FPScited by 113
  21. 20243D Geometry-aware Deformable Gaussian Splatting for Dynamic View Synthesiscited by 109
  22. 2024Per-Gaussian Embedding-Based Deformation for Deformable 3D Gaussian Splattingcited by 104
  23. 2024Motion-aware 3D Gaussian Splatting for Efficient Dynamic Scene Reconstructioncited by 100
  24. 20234K4D: Real-Time 4D View Synthesis at 4K Resolutioncited by 91
  25. 2022R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesiscited by 69
  26. 2023Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstructioncited by 61
  27. 2024Grid4D: 4D Decomposed Hash Encoding for High-Fidelity Dynamic Gaussian Splattingcited by 49
  28. 2024Trimming the Fat: Efficient Compression of 3D Gaussian Splats through Pruningcited by 47
  29. 2024MEGA: Memory-Efficient 4D Gaussian Splatting for Dynamic Scenescited by 47
  30. 2025Swift4D:Adaptive divide-and-conquer Gaussian Splatting for compact and efficient reconstruction of dynamic scenecited by 42
  31. 2024EfficientGS: Streamlining Gaussian Splatting for Large-Scale High-Resolution Scene Representationcited by 27

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 8.

13 papers.

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