{"id":"https://openalex.org/W4417113933","doi":"https://doi.org/10.1145/3769748.3773346","title":"A Survey for Point Prompt of Segment Anything Model","display_name":"A Survey for Point Prompt of Segment Anything Model","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417113933","doi":"https://doi.org/10.1145/3769748.3773346"},"language":null,"primary_location":{"id":"doi:10.1145/3769748.3773346","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769748.3773346","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3769748.3773346","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Multimedia in Asia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3769748.3773346","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005723047","display_name":"Yizai Yang","orcid":"https://orcid.org/0009-0007-9708-7059"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yizai Yang","raw_affiliation_strings":["Hefei University of Technology, Hefei City, Anhui Province, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei City, Anhui Province, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060524512","display_name":"Lechao Cheng","orcid":"https://orcid.org/0000-0002-7546-9052"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lechao Cheng","raw_affiliation_strings":["Hefei University of Technology, Hefei City, Anhui Province, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei City, Anhui Province, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101651167","display_name":"Yaxiong Wang","orcid":"https://orcid.org/0000-0001-6596-8117"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxiong Wang","raw_affiliation_strings":["Hefei University of Technology, Anhui Province, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Anhui Province, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056811650","display_name":"Tianrui Hui","orcid":"https://orcid.org/0000-0002-1172-1554"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Hui","raw_affiliation_strings":["Hefei University of Technology, Hefei City, Anhui Province, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei City, Anhui Province, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010490908","display_name":"Wenjing Li","orcid":"https://orcid.org/0000-0003-3201-6675"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Li","raw_affiliation_strings":["Hefei University of Technology, Hefei City, Anhui Province, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei City, Anhui Province, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065328976","display_name":"Zhun Zhong","orcid":"https://orcid.org/0000-0002-8202-0544"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhun Zhong","raw_affiliation_strings":["Hefei University of Technology, Hefei City, Anhui Province, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei City, Anhui Province, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5005723047"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4212994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4277999997138977,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.4277999997138977,"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"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.1462000012397766,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.09989999979734421,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6243000030517578},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5752000212669373},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5471000075340271},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5425999760627747},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5194000005722046},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4666000008583069},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.3993000090122223}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6370000243186951},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6243000030517578},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5752000212669373},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5425999760627747},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5194000005722046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4950000047683716},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4666000008583069},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41519999504089355},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.41499999165534973},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.3993000090122223},{"id":"https://openalex.org/C41426520","wikidata":"https://www.wikidata.org/wiki/Q1192065","display_name":"Point estimation","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29840001463890076},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C42475967","wikidata":"https://www.wikidata.org/wiki/Q194292","display_name":"Operations research","level":1,"score":0.27379998564720154},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.257099986076355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3769748.3773346","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769748.3773346","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3769748.3773346","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Multimedia in Asia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3769748.3773346","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3769748.3773346","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3769748.3773346","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM International Conference on Multimedia in Asia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4417113933.pdf","grobid_xml":"https://content.openalex.org/works/W4417113933.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W4390874575","https://openalex.org/W4391021462","https://openalex.org/W4394597311","https://openalex.org/W4402754258","https://openalex.org/W4403069407","https://openalex.org/W4403150237","https://openalex.org/W4406458238","https://openalex.org/W4407358421","https://openalex.org/W4407825659","https://openalex.org/W4409346510","https://openalex.org/W4409890298","https://openalex.org/W4410152958","https://openalex.org/W4413147345","https://openalex.org/W4413257806"],"related_works":[],"abstract_inverted_index":{"The":[0],"Segment":[1],"Anything":[2],"Model":[3],"(SAM)":[4],"has":[5],"emerged":[6],"as":[7,75],"a":[8,120],"foundational":[9],"vision":[10],"model":[11],"with":[12],"strong":[13],"zero-shot":[14],"segmentation":[15],"capabilities.":[16],"Among":[17],"its":[18],"prompt":[19,54,61],"modalities,":[20],"point":[21,46,83],"prompts":[22,84],"are":[23],"particularly":[24],"notable":[25],"for":[26,48,123],"their":[27],"simplicity,":[28],"efficiency,":[29],"and":[30,57,60,65,80,88,101,109,114,129],"effectiveness":[31],"in":[32,72,127],"conveying":[33],"user":[34],"intent.":[35],"This":[36,117],"survey,":[37],"to":[38],"our":[39],"knowledge":[40],"the":[41],"first":[42],"dedicated":[43],"review":[44],"on":[45],"prompting":[47],"SAM,":[49],"categorizes":[50],"existing":[51],"approaches":[52],"into":[53],"generation":[55],"(manual":[56],"automatic":[58],"strategies)":[59],"optimization":[62],"(refinement,":[63],"priors":[64],"multimodal":[66],"extensions).":[67],"We":[68],"further":[69],"highlight":[70],"applications":[71],"domains":[73],"such":[74],"medical":[76],"imaging,":[77],"remote":[78],"sensing,":[79],"robotics,":[81],"where":[82],"reduce":[85],"annotation":[86],"cost":[87],"improve":[89],"adaptability.":[90],"Finally,":[91],"we":[92],"discuss":[93],"key":[94],"challenges\u2014standardized":[95],"evaluation,":[96],"fine-boundary":[97],"ambiguity,":[98],"3D":[99],"adaptation,":[100],"uncertainty":[102],"modeling\u2014and":[103],"outline":[104],"future":[105],"directions":[106],"including":[107],"learned":[108],"probabilistic":[110],"prompting,":[111],"multi-modal":[112],"integration,":[113],"benchmark":[115],"design.":[116],"work":[118],"provides":[119],"structured":[121],"roadmap":[122],"advancing":[124],"point-prompt":[125],"engineering":[126],"SAM":[128],"related":[130],"foundation":[131],"models.":[132]},"counts_by_year":[],"updated_date":"2026-03-10T14:07:55.174380","created_date":"2025-12-08T00:00:00"}
