MAVSD：A Multi-Angle View Segmentation Dataset for Detection of Solidago Canadensis L

MAVSD (Multi-Angle View Segmentation Dataset) is a comprehensive multi-angle aerial dataset specifically designed for detecting and segmenting Solidago canadensis L., a widespread invasive plant species. The dataset features high-resolution RGB imagery captured by DJI M300 UAV from four distinct viewing angles (30°, 45°, 60°, and 90°), providing comprehensive coverage of the target plant's morphological characteristics in natural environments. The dataset encompasses 13 semantic categories, including the invasive species, various vegetation types, and common terrain features. All images are provided with dual annotation formats: VOC format classification labels and polygon-based semantic segmentation annotations (JSON+PNG format). The dataset is divided into training and testing sets, with corresponding file lists for each viewing angle. MAVSD's multi-angle acquisition strategy and detailed semantic annotations make it particularly suitable for developing deep learning models for invasive species monitoring and ecological surveys in real-world applications.

This dataset aims to address the challenges in automated vegetation monitoring by providing diverse perspectives and high-quality annotations, facilitating the development of more robust and accurate detection systems for invasive species management.