BUP-ST20: Weakly Labelled Spatial Temporal Sweet Pepper Datahttps://doi.org/10.60507/FK2/NUMVO1Guclu, EsraHalstead, MichaelDenman, SimonMcCool, Chrisbonndata2025-10-062025-10-13T09:54:43ZAccurate monitoring of crop phenotypic traits is essential for efficient farm management and automation in agriculture. Multi-object tracking (MOT) and video instance segmentation (VIS) offer promising approaches to enhance agricultural robotic vision systems, yet a major limitation is the scarcity of high-quality spatial-temporal datasets. We introduce BUP-ST20, a novel weakly labelled spatial-temporal dataset for sweet pepper tracking and segmentation captured on a robotic platform. BUP-ST20 contains 16,240 images from 275 sequences, each with bounding boxes, instance segmentation masks, and temporal identities.The dataset has weakly labelled training and validation sets, while the evaluation set includes 3810 frames with hand-labelled ground truth annotations.Agricultural SciencesEnglishGuclu E, Halstead M, Denman S, McCool C. Weakly labelled spatial-temporal sweet pepper data: Enabling higher quality detection, segmentation, and tracking. The International Journal of Robotics Research. 2025;0(0). doi:10.1177/02783649251379093, doi, 10.1177/02783649251379093, https://doi.org/10.1177/027836492513790932025-10-06Güclü, EsraAgricultural Robotics GroupGuclu EsraHalstead MichaelMcCool ChrisDenman Simon2025-09-292020-09-242020-10-01ImagesNumericalSpreadsheetStructuredQualitativeCC BY 4.0