HAL3D: Hierarchical Active Learning for Fine-Grained 3D Part Labeling

arXiv:2301.10460v2 Announce Type: replace
Abstract: We present the first active learning tool for fine-grained 3D part labeling, a problem which challenges even the most advanced deep learning (DL) methods due to the significant structural variations among the small and intricate parts. For the same reason, the necessary data annotation effort is tremendous, motivating approaches to minimize human involvement. Our labeling tool iteratively verifies or modifies part labels predicted by a deep neural network, with human feedback continually improving the network …

abstract active learning advanced annotation arxiv challenges cs.cv data data annotation deep learning fine-grained hierarchical labeling part reason small tool type