Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models. (arXiv:2304.07221v1 [cs.CV])

Recently, pre-trained point cloud models have found extensive applications in
downstream tasks like object classification. However, these tasks often require
{full fine-tuning} of models and lead to storage-intensive procedures, thus
limiting the real applications of pre-trained models. Inspired by the great
success of visual prompt tuning (VPT) in vision, we attempt to explore prompt
tuning, which serves as an efficient alternative to full fine-tuning for
large-scale models, to point cloud pre-trained models to reduce storage costs.
However, it is non-trivial …

applications apply arxiv classification cloud costs dynamic fine-tuning large-scale models pre-trained models prompt prompt tuning reduce scale storage success vision