{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/abc-a-big-cad-model-dataset-for-geometric","title":"ABC: A Big CAD Model Dataset For Geometric Deep Learning","arxiv_id":"1812.06216","date":"2018-12-15","proceeding":"CVPR 2019 6","authors":["Sebastian Koch","Albert Matveev","Zhongshi Jiang","Francis Williams","Alexey Artemov","Evgeny Burnaev","Marc Alexa","Denis Zorin","Daniele Panozzo"],"abstract":"We introduce ABC-Dataset, a collection of one million Computer-Aided Design\n(CAD) models for research of geometric deep learning methods and applications.\nEach model is a collection of explicitly parametrized curves and surfaces,\nproviding ground truth for differential quantities, patch segmentation,\ngeometric feature detection, and shape reconstruction. Sampling the parametric\ndescriptions of surfaces and curves allows generating data in different formats\nand resolutions, enabling fair comparisons for a wide range of geometric\nlearning algorithms. As a use case for our dataset, we perform a large-scale\nbenchmark for estimation of surface normals, comparing existing data driven\nmethods and evaluating their performance against both the ground truth and\ntraditional normal estimation methods.","url_abs":"http://arxiv.org/abs/1812.06216v2","url_pdf":"http://arxiv.org/pdf/1812.06216v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"abc-a-big-cad-model-dataset-for-geometric","repo_url":"https://github.com/LebronGG/PointCnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"abc-a-big-cad-model-dataset-for-geometric","repo_url":"https://github.com/c3210927/point_cnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"abc-a-big-cad-model-dataset-for-geometric","repo_url":"https://github.com/yangyanli/PointCNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[{"slug":"abc-dataset-1","name":"ABC Dataset","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1812.06216","atlas_url":"https://app.syntology.ai/?focus=1812.06216","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}