Evaluating Deep Clustering Algorithms on Non-Categorical 3D CAD Models

arXiv:2404.19134v1 Announce Type: new
Abstract: We introduce the first work on benchmarking and evaluating deep clustering algorithms on large-scale non-categorical 3D CAD models. We first propose a workflow to allow expert mechanical engineers to efficiently annotate 252,648 carefully sampled pairwise CAD model similarities, from a subset of the ABC dataset with 22,968 shapes. Using seven baseline deep clustering methods, we then investigate the fundamental challenges of evaluating clustering methods for non-categorical data. Based on these challenges, we propose a novel …

abstract algorithms arxiv benchmarking cad categorical clustering cs.cv dataset engineers expert scale type work workflow