English

Key Patch Proposer: Key Patches Contain Rich Information

Computer Vision and Pattern Recognition 2024-02-20 v1

Abstract

In this paper, we introduce a novel algorithm named Key Patch Proposer (KPP) designed to select key patches in an image without additional training. Our experiments showcase KPP's robust capacity to capture semantic information by both reconstruction and classification tasks. The efficacy of KPP suggests its potential application in active learning for semantic segmentation. Our source code is publicly available at https://github.com/CA-TT-AC/key-patch-proposer.

Keywords

Cite

@article{arxiv.2402.11458,
  title  = {Key Patch Proposer: Key Patches Contain Rich Information},
  author = {Jing Xu and Beiwen Tian and Hao Zhao},
  journal= {arXiv preprint arXiv:2402.11458},
  year   = {2024}
}

Comments

Accepted by ICLR 2024 Tiny Papers (notable)

R2 v1 2026-06-28T14:52:06.232Z