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Research questionHow can 3D tokenizers preserve reconstruction fidelity with extremely short token sequences?Existing 3D tokenizers can lose substantial reconstruction quality when their latent representations are compressed to extremely low token budgets. Spatial representations and fixed-size global-token sets may both struggle to preserve complete object geometry under this constraint.
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Latest papersRecent research connected to this question, newest first.ZipTok3D: High-Fidelity 3D Tokenization with Compact Token PrefixesThe source presents ZipTok3D, which uses progressively informative global-token prefixes, trains retained prefixes to reconstruct complete objects, and iteratively decodes them. Evidence is reported on ShapeNet and TRELLIS, including comparisons with a 32-token COD-VAE baseline.research paper · Sep 1, 2026
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