A new learned volume-compression system called EVOLVE targets high compression ratios for scientific simulation data without the per-volume tuning cost of implicit neural methods. Built around an autoencoder and variable-rate encoding, it aims to preserve fine structure while letting one model cover a wide range of compression settings at inference time. For teams working with volumetric pipelines, it points to faster offline compression and more practical deployment than INR-based approaches.
arXiv cs.GR
arXiv cs.GR
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