{"url":"/dataset/primitive-shape-abstraction","name":"Primitive Shape Abstraction","full_name":null,"description_markdown":"# Dataset: RGB-D Images for Real-World and Synthetic Object Scenes\r\n\r\nThis dataset consists of both real-world and synthetic RGB-D images, designed for object detection, classification, and segmentation tasks, particularly for primitive shape recognition. \r\n\r\n## Real-World Data\r\n\r\n- **Objects**: 50 distinct objects captured using a Kinect camera.\r\n- **Scenes**: The dataset includes both single objects and piles of objects stacked over each other.\r\n- **Images**: Approximately 300 RGB-D images have been collected.\r\n- **Data Format**: RGB images paired with corresponding depth images.\r\n\r\n## Synthetic Data\r\n\r\n- **Simulator**: The synthetic dataset was automatically generated using the CoppeliaSim simulator.\r\n- **Objects**: Only primitive shapes, including cuboid, semisphere, sphere, cylinder, stick, ring, and cone.\r\n- **Scenes**: Objects are dropped over each other to form complex scenes.\r\n- **Images**: The dataset contains 10,000 unique RGB-D images generated by the simulator.\r\n\r\n## Labels\r\n\r\nBoth the real-world and synthetic datasets are labeled with geometric primitive shape classes and boundaries, including:\r\n\r\n- Cuboid\r\n- Semisphere\r\n- Sphere\r\n- Cylinder\r\n- Stick\r\n- Ring\r\n- Cone\r\n\r\nThis dataset is designed to support research in grasp detection, object recognition, and scene understanding using RGB-D data.","description_withheld":null,"homepage":"","introduced_date":"2024-09-16","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"Image Segmentation","url":"/task/image-segmentation","datasets_with_task":"/datasets/task/image-segmentation"},{"name":"Robotic Grasping","url":"/task/robotic-grasping","datasets_with_task":"/datasets/task/robotic-grasping"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Primitive Shape Abstraction"],"data_loaders":[],"num_papers_in_archive":0,"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."}