{"id":"https://openalex.org/W7138845650","doi":"https://doi.org/10.48550/arxiv.2603.16270","title":"MG-Grasp: Metric-Scale Geometric 6-DoF Grasping Framework with Sparse RGB Observations","display_name":"MG-Grasp: Metric-Scale Geometric 6-DoF Grasping Framework with Sparse RGB Observations","publication_year":2026,"publication_date":"2026-03-17","ids":{"openalex":"https://openalex.org/W7138845650","doi":"https://doi.org/10.48550/arxiv.2603.16270"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.16270","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16270","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.16270","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129778034","display_name":"Kangxu Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Kangxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062232744","display_name":"Siang Chen","orcid":"https://orcid.org/0000-0002-9235-6439"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Siang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026214170","display_name":"Chenxing Jiang","orcid":"https://orcid.org/0000-0002-0470-9784"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Chenxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001947944","display_name":"Shaojie Shen","orcid":"https://orcid.org/0000-0002-5573-2909"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Shaojie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089449805","display_name":"Yixiang Dai","orcid":"https://orcid.org/0009-0000-7501-5504"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dai, Yixiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5045183950","display_name":"Guijin Wang","orcid":"https://orcid.org/0000-0002-2131-3044"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guijin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10653","display_name":"Robot Manipulation and Learning","score":0.9542999863624573,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.9542999863624573,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.010700000450015068,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10982","display_name":"Motor Control and Adaptation","score":0.00559999980032444,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.942300021648407},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5950999855995178},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5856000185012817},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5849000215530396},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5490000247955322},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.510699987411499},{"id":"https://openalex.org/keywords/robotic-hand","display_name":"Robotic hand","score":0.4754999876022339}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.942300021648407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8112000226974487},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.800599992275238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6980999708175659},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5950999855995178},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5849000215530396},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5490000247955322},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.510699987411499},{"id":"https://openalex.org/C2988191880","wikidata":"https://www.wikidata.org/wiki/Q40687","display_name":"Robotic hand","level":3,"score":0.4754999876022339},{"id":"https://openalex.org/C2775960376","wikidata":"https://www.wikidata.org/wiki/Q1435859","display_name":"Grippers","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.35920000076293945},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.31619998812675476},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2619999945163727}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.16270","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16270","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.16270","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.16270","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Single-view":[0],"RGB-D":[1],"grasp":[2,22,44,104],"detection":[3],"remains":[4],"a":[5,16,53],"common":[6],"choice":[7],"in":[8],"6-DoF":[9,21,56,89,108],"robotic":[10,39],"grasping":[11,57,109],"systems,":[12],"which":[13],"typically":[14],"requires":[15],"depth":[17],"sensor.":[18],"While":[19],"RGB-only":[20],"methods":[23],"has":[24],"been":[25],"studied":[26],"recently,":[27],"their":[28],"inaccurate":[29],"geometric":[30],"representation":[31],"is":[32],"not":[33],"directly":[34],"suitable":[35],"for":[36],"physically":[37],"reliable":[38,43],"manipulation,":[40],"thereby":[41],"hindering":[42],"generation.":[45],"To":[46],"address":[47],"these":[48],"limitations,":[49],"we":[50],"propose":[51],"MG-Grasp,":[52],"novel":[54],"depth-free":[55],"framework":[58],"that":[59,99],"achieves":[60,101],"high-quality":[61],"object":[62],"grasping.":[63],"Leveraging":[64],"two-view":[65],"3D":[66],"foundation":[67],"model":[68],"with":[69],"camera":[70],"intrinsic/extrinsic,":[71],"our":[72],"method":[73],"reconstructs":[74],"metric-scale":[75],"and":[76,86,95],"multi-view":[77],"consistent":[78],"dense":[79],"point":[80],"clouds":[81],"from":[82],"sparse":[83],"RGB":[84],"images":[85],"generates":[87],"stable":[88],"grasp.":[90],"Experiments":[91],"on":[92],"GraspNet-1Billion":[93],"dataset":[94],"real":[96],"world":[97],"demonstrate":[98],"MG-Grasp":[100],"state-of-the-art":[102],"(SOTA)":[103],"performance":[105],"among":[106],"RGB-based":[107],"methods.":[110]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-20T00:00:00"}
