{"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/3d-reconstruction-of-incomplete","title":"3D Reconstruction of Incomplete Archaeological Objects Using a Generative Adversarial Network","arxiv_id":"1711.06363","date":"2017-11-17","proceeding":null,"authors":["Renato Hermoza","Ivan Sipiran"],"abstract":"We introduce a data-driven approach to aid the repairing and conservation of\narchaeological objects: ORGAN, an object reconstruction generative adversarial\nnetwork (GAN). By using an encoder-decoder 3D deep neural network on a GAN\narchitecture, and combining two loss objectives: a completion loss and an\nImproved Wasserstein GAN loss, we can train a network to effectively predict\nthe missing geometry of damaged objects. As archaeological objects can greatly\ndiffer between them, the network is conditioned on a variable, which can be a\nculture, a region or any metadata of the object. In our results, we show that\nour method can recover most of the information from damaged objects, even in\ncases where more than half of the voxels are missing, without producing many\nerrors.","url_abs":"http://arxiv.org/abs/1711.06363v2","url_pdf":"http://arxiv.org/pdf/1711.06363v2.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":"3d-reconstruction-of-incomplete","repo_url":"https://github.com/renato145/3D-ORGAN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"3d-reconstruction","task_name":"3D Reconstruction"},{"task_slug":"culture","task_name":"Cultural Vocal Bursts Intensity Prediction"},{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":null,"task_name":"Generative Adversarial Network"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-reconstruction","task_name":"Object Reconstruction"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1711.06363","atlas_url":"https://app.syntology.ai/?focus=1711.06363","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}