Auditing Training-Free 3D Shape Retrieval with Diffused Geodesic Moments 事件

Auditing Training-Free 3D Shape Retrieval with Diffused Geodesic Moments arXiv:2605.29004v1 Announce Type: new Abstract: Reported retrieval scores for training-free shape descriptors conflate local signal design, normalization, aggregation, codebook fitting, and metric choices, making isolated component evaluation difficult. This paper reframes descriptor evaluation as a {\em protocol audit}. We introduce Diffused Geodesic Moments (DGM), a seed-conditioned descriptor that computes sparse implic