{"type":"ScholarlyArticle","title":"Bottleneck Identification to Semantic Segmentation of Industrial 3D Point Cloud Scene via Deep Learning","authors":[{"name":"Romain Cazorla","slug":"romain-cazorla","given":"Romain","family":"Cazorla","affiliation":""},{"name":"Line Poinel","slug":"line-poinel","given":"Line","family":"Poinel","affiliation":""},{"name":"Panagiotis Papadakis","slug":"panagiotis-papadakis","given":"Panagiotis","family":"Papadakis","affiliation":""},{"name":"Cédric Buche","slug":"cedric-buche","given":"Cédric","family":"Buche","affiliation":""}],"abstract":"Point cloud acquisition techniques are an essential tool for the digitization of industrial plants, yet the bulk of a designer's work remains manual. A first step to automatize drawing generation is to extract the semantics of the point cloud. Towards this goal, we investigate the use of deep learning to semantically segment oil and gas industrial scenes. We focus on domain characteristics such as high variation of object size, increased concavity and lack of annotated data, which hampers the use of conventional approaches. To address these issues, we advocate the use of synthetic data, adaptive downsampling and context sharing.","doi":"10.24963/ijcai.2021/670","url":"https://ijcai.org/proceedings/2021/670","pdf":"https://ijcai.org/proceedings/2021/0670.pdf","markdown":"https://ijcai.org/proceedings/2021/670.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/670","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":670,"pages":{"first":4877,"last":4878},"keywords":["Computer Vision: Recognition: Detection, Categorization, Indexing, Matching, Retrieval, Semantic Interpretation","Machine Learning Applications: Applications of Supervised Learning","Computer Vision: 2D and 3D Computer Vision","Machine Learning: Deep Learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}