首个融合植物分类的细粒度计数数据集,支持百种植物自动计数。
Plant Taxonomy Meets Plant Counting: A Fine-Grained, Taxonomic Dataset for Counting Hundreds of Plant Species
- 构建包含268个物种的植物计数数据集,带分类标签与器官标注
- 涵盖10,000张图像、678,050个点标注,覆盖从宏观到微观尺度
- 适用于生物多样性研究、自动化植物统计,适合计算机视觉与生态学交叉研究
视觉化记录和量化自然世界需要在精细视觉分类与大规模计数上持续突破。尽管在人群与交通分析中取得显著进展,植物的细粒度、分类感知计数仍处于探索阶段。与人群不同,植物具有非刚性形态及生长阶段和环境带来的外观差异。为填补这一空白,我们提出TPC-268,首个融合植物分类的植物计数基准。该数据集结合实例级点标注与林奈分类标签(界→种)及器官类别,支持层级推理与物种感知评估。数据集包含10,000张图像、678,050个点标注,涵盖242个植物与真菌物种的268个可计数类别,覆盖冠层遥感至组织显微镜等多尺度观测。采用无类别计数(CAC)任务设置,提供分类一致、尺度感知的数据划分,并对主流回归与检测类CAC方法进行基准测试。通过捕捉生物与真菌类群的多样性、层级结构与多尺度特性,TPC-268为细粒度无类别计数提供生物学基础测试平台。数据集与代码见https://github.com/tiny-smart/TPC-268。
原文摘要 · Abstract (English)
Visually cataloging and quantifying the natural world requires pushing the boundaries of both detailed visual classification and counting at scale. Despite significant progress, particularly in crowd and traffic analysis, the fine-grained, taxonomy-aware plant counting remains underexplored in vision. In contrast to crowds, plants exhibit nonrigid morphologies and physical appearance variations across growth stages and environments. To fill this gap, we present TPC-268, the first plant counting benchmark incorporating plant taxonomy. Our dataset couples instance-level point annotations with Linnaean labels (kingdom -> species) and organ categories, enabling hierarchical reasoning and species-aware evaluation. The dataset features 10,000 images with 678,050 point annotations, includes 268 countable plant categories over 242 plant species in Plantae and Fungi, and spans observation scales from canopy-level remote sensing imagery to tissue-level microscopy. We follow the problem setting of class-agnostic counting (CAC), provide taxonomy-consistent, scale-aware data splits, and benchmark state-of-the-art regression- and detection-based CAC approaches. By capturing the biodiversity, hierarchical structure, and multi-scale nature of botanical and mycological taxa, TPC-268 provides a biologically grounded testbed to advance fine-grained class-agnostic counting. Dataset and code are available at https://github.com/tiny-smart/TPC-268.
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