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QuantizationGS: Differentiable quantization model for 3D Gaussian Splatting compression
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AI
DOI：10.1016/j.cag.2026.104596.png)
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Abstract
En 中文
• Compress the model by injecting quantization noise into the parameters during training. • Prune redundant anchor points using a global importance scoring mechanism to improve rendering speed. • Maintain reconstruction quality through specialized loss constraining model training.
Keywords:
Quantization
Gaussian Splatting
Model Compression
Anchor Point Pruning
Loss Constraining
Journal
C
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0
Papers:
119
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