Data-efficient Event Camera Pre-training via Disentangled Masked Modeling

arXiv:2403.00416v1 Announce Type: new
Abstract: In this paper, we present a new data-efficient voxel-based self-supervised learning method for event cameras. Our pre-training overcomes the limitations of previous methods, which either sacrifice temporal information by converting event sequences into 2D images for utilizing pre-trained image models or directly employ paired image data for knowledge distillation to enhance the learning of event streams. In order to make our pre-training data-efficient, we first design a semantic-uniform masking method to address the learning imbalance …

abstract arxiv cameras cs.cv data event image image data images information limitations modeling paper pre-training self-supervised learning supervised learning temporal training type via voxel