{"url":"/dataset/pu1k","name":"PU1K","full_name":null,"description_markdown":"PU1K is nearly 8 times larger than the largest publicly available dataset collected by PU-GAN. PU1K consists of 1,147 3D models split into 1020 training samples and 127 testing samples. The training set contains 120 3D models compiled from PU-GAN’s dataset, in addition to 900 different models collected from ShapeNetCore. The testing set contains 27 models from PU-GAN and 100 more models from ShapeNetCore.","description_withheld":null,"homepage":"https://github.com/guochengqian/PU-GCN","introduced_date":"2021-06-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/pu-gcn-point-cloud-upsampling-using-graph","title":"PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks","first_author":"Guocheng Qian","url":null},"license":null,"modalities":[{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"point cloud upsampling","url":"/task/point-cloud-upsampling","datasets_with_task":"/datasets/task/point-cloud-upsampling"}],"languages":[],"variants":["PU1K"],"data_loaders":[],"num_papers_in_archive":18,"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."}