{"url":"/dataset/cropandweed-dataset","name":"CropAndWeed","full_name":null,"description_markdown":"The CropAndWeed dataset is focused on the fine-grained identification of 74 relevant crop and weed species with a strong emphasis on data variability. Annotations of labeled bounding boxes, semantic masks and stem positions are provided for about 112k instances in more than 8k high-resolution images of both real-world agricultural sites and specifically cultivated outdoor plots of rare weed types. Additionally, each sample is enriched with meta-annotations regarding environmental conditions.","description_withheld":null,"homepage":"https://github.com/cropandweed/cropandweed-dataset","introduced_date":"2023-01-06","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-cropandweed-dataset-a-multi-modal","title":"The CropAndWeed Dataset: A Multi-Modal Learning Approach for Efficient Crop and Weed Manipulation","first_author":"Daniel Steininger","url":null},"license":{"name":"Custom (non-commercial)","url":"https://github.com/cropandweed/cropandweed-dataset/blob/main/LICENCE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Domain Adaptation","url":"/task/domain-adaptation","datasets_with_task":"/datasets/task/domain-adaptation"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"},{"name":"Fine-Grained Image Classification","url":"/task/fine-grained-image-classification","datasets_with_task":"/datasets/task/fine-grained-image-classification"},{"name":"Panoptic Segmentation","url":"/task/panoptic-segmentation","datasets_with_task":"/datasets/task/panoptic-segmentation"},{"name":"Multi-Task Learning","url":"/task/multi-task-learning","datasets_with_task":"/datasets/task/multi-task-learning"},{"name":"Crop Classification","url":"/task/crop-classification","datasets_with_task":"/datasets/task/crop-classification"},{"name":"Benchmarking","url":"/task/benchmarking","datasets_with_task":"/datasets/task/benchmarking"},{"name":"Crop Yield Prediction","url":"/task/crop-yield-prediction","datasets_with_task":"/datasets/task/crop-yield-prediction"},{"name":"Plant Phenotyping","url":"/task/plant-phenotyping","datasets_with_task":"/datasets/task/plant-phenotyping"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["CropAndWeed"],"data_loaders":[{"repo":"https://github.com/cropandweed/cropandweed-dataset","url":"https://github.com/cropandweed/cropandweed-dataset","frameworks":[]},{"repo":"https://github.com/Daraan/CropAndWeedDetection","url":"https://github.com/Daraan/CropAndWeedDetection","frameworks":[]}],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}