CropAndWeedandLeaf is a dataset to benchmark leaf-segmentation models across multiple plant species, as described in the corresponding ReLeaf paper, presented at the Agriculture-Vision Workshop at CVPR 2026. The dataset is based on images from the CropAndWeed dataset, which are cropped to individual plant instances and enhanced with instance-segmentation masks for individual leaves. Source code, models and further documentation can be found on our GitHub page. Data Structure The repository provides the following subdirectories: images: cropped images containing all annotated plant instances labels: annotations corresponding to each image in YOLOv8 instance-segmentation format Plant Species The label IDs correspond to the original labels defined in the CropAndWeed dataset. 1: Maize (Zea mays) 7: Sugar beet (Beta vulgaris s. vulgaris) 13: Pea (Pisum sativum) 14: Zucchini (Cucurbita pepo var. gir.) 15: Squash (Cucurbita) 18: Potato (Solanum tuberosum) 22: Poppy (Papaver) 24: Common sunflower (Helianthus annuus) 26: Common bean (Phaseolus vulgaris) 27: Broad bean (Vicia faba) 29: Maple-leaf goosefoot (Chenopodium hybridum) 30: Black-bindweed (Fallopia convolvulus) 32: Red-root amaranth (Amaranthus retroflexus) 33: White goosefoot (Chenopodium album) 34: Thornapple (Datura stramonium) 38: Creeping thistle (Cirsium arvense) 39: Field sowthistle (Sonchus arvensis) 66: Redshank (Persicaria maculosa) 71: Cornflower (Centaurea cyanus) 72: Common corncockle (Agrostemma githago) 77: Ribwort plantain (Plantago lanceolata) 89: Copse bindweed (Fallopia dumetorum) 94: Soybean (Glycine max) File Naming Convention File names of images and annotations extend the image names in CropAndWeed with the row number of the extracted plant in the original object-detection annotations: <subset>-<session>-<image>-<row> Example ave-0045-0011-012: subset ave, session 45, image 11, the plant was extracted from row 12 of the corresponding csv-file (object detection) Citing If you use the CropAndWeedAndLeaf benchmark for your research, please cite the original paper: Martinko, R., Steininger, D., Simon, J., Trondl, A., Blaickner, M., 2026. ReLeaf: Benchmarking Leaf Segmentation across Domains and Species. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.