Annotation-Free Furniture Codes: What They Encode, and How Far They Transfer
Layout-based 3D scene synthesizers place each object using two human-annotated channels: a categorical class label and a canonical-pose convention. We ask whether a single self-supervised token derived from object geometry can replace both, and study such tokens directly as a representation, decoupled from any synthesizer. A Finite Scalar Quantization (FSQ) point-cloud autoencoder is chamfer-trained on placed 3D-FUTURE furniture with no labels or pose annotations. Diagnostic probes recover fine-
Record details
Published: 11 July 2026
Source: arXiv
Category: Research
Topics: Healthcare
Retrieved: 14 July 2026
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ethics.ai (11 July 2026), “Annotation-Free Furniture Codes: What They Encode, and How Far They Transfer,” evidence record 42, https://ethics.ai/record/42 (originally published by arXiv).
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