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arXiv cs.GR
arXiv cs.GR Research
· 9 months, 4 weeks ago • Saqib Javed, Ahmad Jarrar Khan, Corentin Dumery, Chen Zhao, Mathieu Salzmann

Temporally Compressed 3D Gaussian Splatting for Dynamic Scenes

Briefing

The introduction of Temporally Compressed 3D Gaussian Splatting (TC3DGS) marks a significant advancement in dynamic scene reconstruction. By selectively pruning Gaussians based on their temporal relevance and employing gradient-aware mixed-precision quantization, TC3DGS achieves remarkable compression rates of up to 67 times. This is particularly beneficial for developers working on AR/VR and gaming applications, where memory efficiency and rendering speed are critical.

The technique also utilizes an adapted Ramer-Douglas-Peucker algorithm to interpolate Gaussian trajectories across frames, further enhancing storage efficiency. With minimal or no degradation in visual quality, TC3DGS positions itself as a game-changer for developers aiming to optimize performance on low-power devices while maintaining high-fidelity graphics.

“Achieves up to 67 times compression with minimal visual quality loss.”

— Research Team · Summary of TC3DGS results
Original source
Read on arXiv cs.GR
At a glance
what
Introduction of Temporally Compressed 3D Gaussian Splatting (TC3DGS)
who
Developed by Ahmad Jarrar
impact
Enables real-time applications in AR/VR and gaming with improved efficiency
context
Addresses challenges in rendering complex dynamic scenes
Signal Positive

Promising advancements in efficiency for developers

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