Key Patch Proposer: Key Patches Contain Rich Information
<|reference_start|>Key Patch Proposer: Key Patches Contain Rich Information: 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.<|reference_end|>
@article{xu2024key,
    title={Key Patch Proposer: Key Patches Contain Rich Information},
    author={Jing Xu, Beiwen Tian, Hao Zhao},
    journal={arXiv preprint arXiv:2402.11458},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.11458},
    primaryClass={cs.CV}
}