{"url":"/dataset/xa-dateset","name":"XA Bin-Picking","full_name":null,"description_markdown":"**XA Bin-Picking** is a point-cloud dataset comprising both simulated and real-world scenes with three industrial parts.  Synthesized scenes consists of 1000 training samples. The test samples are real scenes and the ground\r\ntruth instance labels are made manually. There are 20 to\r\n30 identical types of parts randomly piled up in a scene.\r\nEach scene contains about 60,000 boundary points. Each\r\npoint in the scene has instance annotations. The parts are\r\ntexture-less and have no discernible color. Both of training samples and test sam-\r\nples only contain the boundary points of parts.\r\n\r\nSource: [A Convolutional Neural Network for Point Cloud Instance Segmentation in Cluttered Scene Trained by Synthetic Data Without Color](/paper/a-convolutional-neural-network-for-point)\r\nImage Source: [A Convolutional Neural Network for Point Cloud Instance Segmentation in Cluttered Scene Trained by Synthetic Data Without Color](/paper/a-convolutional-neural-network-for-point)","description_withheld":null,"homepage":"https://drive.google.com/drive/folders/1KCDS8_ZHxav5NZKhBzgEX4srf5xg7vW0?usp=sharing","introduced_date":"2020-03-05","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-convolutional-neural-network-for-point","title":"A Convolutional Neural Network for Point Cloud Instance Segmentation in Cluttered Scene Trained by Synthetic Data Without Color","first_author":"Yajun Xu","url":null},"license":null,"modalities":[{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"3D Instance Segmentation","url":"/task/3d-instance-segmentation-1","datasets_with_task":"/datasets/task/3d-instance-segmentation-1"}],"languages":[],"variants":["XA Bin-Picking"],"data_loaders":[],"num_papers_in_archive":1,"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."}