{"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-psrnet-part-segmented-3d-point-cloud","title":"3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image","arxiv_id":"1810.00461","date":"2018-09-30","proceeding":null,"authors":["Priyanka Mandikal","Navaneet K L","R. Venkatesh Babu"],"abstract":"We propose a mechanism to reconstruct part annotated 3D point clouds of\nobjects given just a single input image. We demonstrate that jointly training\nfor both reconstruction and segmentation leads to improved performance in both\nthe tasks, when compared to training for each task individually. The key idea\nis to propagate information from each task so as to aid the other during the\ntraining procedure. Towards this end, we introduce a location-aware\nsegmentation loss in the training regime. We empirically show the effectiveness\nof the proposed loss in generating more faithful part reconstructions while\nalso improving segmentation accuracy. We thoroughly evaluate the proposed\napproach on different object categories from the ShapeNet dataset to obtain\nimproved results in reconstruction as well as segmentation.","url_abs":"http://arxiv.org/abs/1810.00461v1","url_pdf":"http://arxiv.org/pdf/1810.00461v1.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-psrnet-part-segmented-3d-point-cloud","repo_url":"https://github.com/val-iisc/3d-psrnet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"3d-point-cloud-reconstruction","task_name":"3D Point Cloud Reconstruction"},{"task_slug":"point-cloud-reconstruction","task_name":"Point cloud reconstruction"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.00461","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.00461"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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