{"id":"https://openalex.org/W2914845116","doi":"https://doi.org/10.1109/lra.2020.3004802","title":"3D Instance Embedding Learning With a Structure-Aware Loss Function for Point Cloud Segmentation","display_name":"3D Instance Embedding Learning With a Structure-Aware Loss Function for Point Cloud Segmentation","publication_year":2020,"publication_date":"2020-06-25","ids":{"openalex":"https://openalex.org/W2914845116","doi":"https://doi.org/10.1109/lra.2020.3004802","mag":"2914845116"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2020.3004802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2020.3004802","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1902.05247","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhidong Liang","orcid":"https://orcid.org/0000-0001-7947-0248"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhidong Liang","raw_affiliation_strings":["Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7947-0248","affiliations":[{"raw_affiliation_string":"Research Institute of Robotics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ming Yang","orcid":"https://orcid.org/0000-0002-8679-9137"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China","Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8679-9137","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-2185-5433"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Li","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China","Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2185-5433","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chunxiang Wang","orcid":"https://orcid.org/0000-0002-6885-6740"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunxiang Wang","raw_affiliation_strings":["Department of Automation, Shanghai Jiao Tong University, Shanghai, China","Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6885-6740","affiliations":[{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, China","institution_ids":["https://openalex.org/I1327237609"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.1243,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.97763807,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"5","issue":"3","first_page":"4915","last_page":"4922"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9327999949455261,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9327999949455261,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.008500000461935997,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.006200000178068876,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7254999876022339},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6481000185012817},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6453999876976013},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5770999789237976},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5432000160217285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5228000283241272},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.492900013923645},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4634000062942505}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7254999876022339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6601999998092651},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6481000185012817},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6453999876976013},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6122999787330627},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5770999789237976},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5432000160217285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5228000283241272},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.492900013923645},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4634000062942505},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4399000108242035},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37619999051094055},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3400000035762787},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.25119999051094055},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2020.3004802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2020.3004802","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1902.05247","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.05247","pdf_url":"https://arxiv.org/pdf/1902.05247","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1902.05247","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1902.05247","pdf_url":"https://arxiv.org/pdf/1902.05247","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2297757108","display_name":null,"funder_award_id":"U1764264","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2591868390","display_name":null,"funder_award_id":"61873165","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1644641054","https://openalex.org/W1903029394","https://openalex.org/W2211722331","https://openalex.org/W2412782625","https://openalex.org/W2556802233","https://openalex.org/W2560023338","https://openalex.org/W2565639579","https://openalex.org/W2594519801","https://openalex.org/W2749895778","https://openalex.org/W2769312834","https://openalex.org/W2884561390","https://openalex.org/W2904332125","https://openalex.org/W2961368225","https://openalex.org/W2962759414","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2963167763","https://openalex.org/W2963182550","https://openalex.org/W2963226018","https://openalex.org/W2963857746","https://openalex.org/W2964266557","https://openalex.org/W2968474279","https://openalex.org/W2969985801","https://openalex.org/W3004300126","https://openalex.org/W6726946684","https://openalex.org/W6736147098","https://openalex.org/W6736894448","https://openalex.org/W6739778489","https://openalex.org/W6759034663","https://openalex.org/W6763229141","https://openalex.org/W6763422710","https://openalex.org/W6766978945","https://openalex.org/W6785652829","https://openalex.org/W6910567446"],"related_works":[],"abstract_inverted_index":{"This":[0],"letter":[1],"presents":[2],"a":[3],"framework":[4],"for":[5,64,93,124],"3D":[6,13,40,66,75],"instance":[7,27,101,125],"segmentation":[8],"on":[9,120],"point":[10,36],"clouds.":[11],"A":[12],"convolutional":[14],"neural":[15],"network":[16,104],"is":[17,58,82],"used":[18],"as":[19],"the":[20,33,45,54,70,77,86,100],"backbone":[21],"to":[22,32,60,96],"generate":[23],"semantic":[24],"predictions":[25],"and":[26,98],"embeddings":[28,63],"simultaneously.":[29],"In":[30],"addition":[31],"embedding":[34],"information,":[35,53],"clouds":[37],"also":[38],"provide":[39],"geometric":[41],"information":[42],"which":[43],"reflects":[44],"relation":[46],"between":[47],"points.":[48],"Considering":[49],"both":[50],"types":[51],"of":[52],"structure-aware":[55],"loss":[56],"function":[57],"proposed":[59],"achieve":[61],"discriminative":[62],"each":[65],"instance.":[67],"To":[68],"eliminate":[69],"quantization":[71],"error":[72],"caused":[73],"by":[74],"voxel,":[76],"attention-based":[78],"$k$-nearest":[79],"neighbor":[80],"(kNN)":[81],"proposed.":[83],"Different":[84],"from":[85],"average":[87],"strategy,":[88],"it":[89],"learns":[90],"different":[91,94],"weights":[92],"neighbors":[95],"aggregate":[97],"update":[99],"embeddings.":[102],"Our":[103],"can":[105],"be":[106],"trained":[107],"in":[108],"an":[109],"end-to-end":[110],"style.":[111],"Experiments":[112],"show":[113],"that":[114],"our":[115],"approach":[116],"achieves":[117],"state-of-the-art":[118],"performance":[119],"two":[121],"challenging":[122],"datasets":[123],"segmentation.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-02-21T00:00:00"}