Overview
Iyo Swin Transformer chiratidzo cheTransformer chinogadzirisa mifananidzo mukuchinja, hierarchical windows, zvichiita kuti kutarisisa kushande zvakakwana kuyera pamifananidzo yakakwira-resolution. Inoshanda seyakajairwa-chinangwa musana wekurongedza, kuona, uye kupatsanura.
Swin Transformer ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira.
Deep Dive
Standard Vision Transformers inokokorodza kutarisisa kune ese mapeji emifananidzo, ayo anodhura anokura zvakapetwa nekukura kwemufananidzo, chipingamupinyi chemabasa akakora sekuona. Yakaunzwa ne Microsoft Tsvagiridzo muna 2021, Swin (Shifted WINdows) panzvimbo iyoyo inokamura mufananidzo kuita mahwindo madiki asina kupindirana uye inoverengera kutarisisa mukati mehwindo rega rega, zvichiita kuti mutengo ukure zvakatevedzana nekukura kwemufananidzo. Kurega ruzivo ruchiyambuka miganhu yehwindo, mitsara inochinjana ichichinja gidhi rehwindo, saka zvigamba zvakapatsanurwa zvino zvinogovera hwindo. Swin zvakare inovaka humambo: inotanga nemadiki madiki uye zvishoma nezvishoma inoabatanidza, ichigadzira akawanda-scale mamepu akafanana neCNN, ayo anotsvedza zvakatsetseka mukuona aripo uye zvikamu zvezvikamu.
Technical Insight
Kubudirira kweSwin kunobva pahwindo-based multi-head self-attention (W-MSA): kutarisisa kunongogumira kumahwindo akamisikidzwa (semuenzaniso 7x7 zvigamba), saka kuomarara kunoyera mutsara kwete quadratically nenhamba yezvigamba. Iyo inotevera bhuroka inoshandisa yakachinjika-hwindo kutarisa (SW-MSA), ichibvisa iyo hwindo kupatsanurwa nehafu yehwindo saka muchinjika-hwindo rekubatanidza fomu. Patch-yekubatanidza maseru anobatanidza zvigamba zvakavakidzana pakati pematanho, nepakati kugadziriswa kwenzvimbo uye nzira dzakapetwa kaviri kuvaka piramidhi.
Kugona Swin Transformer
Iyo Swin Transformer chiratidzo cheTransformer chinogadzirisa mifananidzo mukuchinja, hierarchical windows, zvichiita kuti kutarisisa kushande zvakakwana kuyera pamifananidzo yakakwira-resolution. Inoshanda seyakajairwa-chinangwa musana wekurongedza, kuona, uye kupatsanura. Swin Transformer ndeyekombuta-yekuona workflows inodudzira kana kugadzira midhiya yekuona yekuongorora, mashandiro, uye kugadzira. Kuti uvake kunzwisisa kwakadzama, bata Swin Transformer semuenzaniso wekushandisa, kwete chinhu chimwe chete: tsanangura zvaunoda mhedzisiro, kujekesa fungidziro, uye patsanura izvo zvinogona kuitwa nehurongwa hwakavimbika kubva kune zvichiri kuda kutonga kwenyanzvi.
Mukuita, zvikwata zvakasimba zvinoshandisa Swin Transformer chiyero chechokwadi nezvinhu zvekushanda semhando yedata, kusiyana kwemwenje, uye kuenderana kwemazita. Ivo vanonyora zvakajeka maitiro ebudiriro, bvunzo vachipokana ne data rechokwadi uye mafambiro ebasa, uye iterate zvichibva pane zvakacherechedzwa maitiro ekutadza kwete kuhwina-nguva imwe chete yebhenji. Apa ndipo apo kunzwisisa kwe theoretical kunoshanduka kuve kugona kwakasimba pane chigadzirwa, mutemo, uye mashandiro.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Panguva imwecheteyo, kodzero dzeMufananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana hunhu husina kujeka. Nzira yakatsiga ndeyekubatanidza kukurumidza kuyedza nekutonga: mhanyisa vatyairi vendege, tora humbowo, buritsa matanda esarudzo, uye urambe uchivandudza chengetedzo semaitiro emuenzaniso, zvinotarisirwa nemushandisi, uye zvinodikanwa zvekutonga.
Strategic Impact
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero.
Visual AI inogona kuita otomatiki yekuongorora, yekuona, uye yekumaka mabasa pachiyero. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma.
Zvikwata zvekugadzira zvinogona prototype pfungwa nekukurumidza nekudzokororwa kwemaoko mashoma. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa.
Mashandisirwo anogona kushandisa masaini emifananidzo nemavhidhiyo ayo aimbove akaoma kugadzirisa. Mukutumirwa kwemhando yepamusoro, izvi zvinoshandurirwa kuita mitemo inoyerwa yekushanda, miganhu yevaridzi, uye tsika dzekudzokorora dzinodzokororwa kuitira kuti zvikwata zvikwire kuvimba pane kukwidza kusajeka.
Real-World Implementation
Yepamusoro-chaiyo ImageNet kupatsanura seyakafanodzidziswa musana
Kuonekwa kwechinhu uye muenzaniso segmentation backbones mune masisitimu seMask R-CNN uye Cascade R-CNN
Semantic segmentation yezviratidziro zvemumugwagwa uye setiraiti mifananidzo
Ongororo yemifananidzo yezvokurapa uko kugadzirisa kwepamusoro uye zvakawanda-zvikero zvine basa
Maitiro Ekuita
Swin Transformer mukuita
Yepamusoro-chaiyo ImageNet kupatsanura seyakafanodzidziswa musana.
Yepamusoro-chaiyo ImageNet kupatsanurwa seyakafanodzidziswa musana Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura emhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Swin Transformer mukuita
Kuonekwa kwechinhu uye semuenzaniso kupatsanurwa kwemashure mumatanho seMask R-CNN uye Cascade R-CNN.
Kuonekwa kwechinhu uye muenzaniso segmentation mabhenekeri muzvirongwa zvakaita seMask R-CNN uye Cascade R-CNN Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura zvikumbaridzo zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Swin Transformer mukuita
Semantic segmentation yezviratidziro zvemumugwagwa uye setiraiti mifananidzo.
Semantic segmentation yezviratidziro zvemumugwagwa uye setiraiti mifananidzo Matimu anowanzo kuwana mhedzisiro iri nani kana achinge atsanangura zvemhando yepamusoro kumberi, chengetedza nzira yekukwira kwevanhu yemakesi emupendero, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Swin Transformer mukuita
Ongororo yemifananidzo yezvokurapa uko kugadzirisa kwepamusoro uye zvakawanda-zvikero zvine basa.
Ongororo yemifananidzo yezvokurapa uko kugadzirisa kwepamusoro uye kwakasiyana-siyana zvine basa Matimu anowanzo kuwana mhedzisiro iri nani kana vachitsanangudza zvikumbaridzo zvemhando yepamusoro, chengetedza nzira yekukwira kwevanhu yemakesi ekumucheto, uye kuteedzera zvese zvakawanikwa zvechigadzirwa uye mutengo wekukanganisa nekufamba kwenguva.
Njodzi & Guardrails
Kodzero dzemifananidzo uye kubvumirwa kunogona kuve njodzi dzepamutemo kana provenance isina kujeka.
Kuita kwemuenzaniso kunogona kusiyanisa kupenya, huwandu hwevanhu, uye nharaunda.
Manyepo enhema anogona kusacherechedzwa kunze kwekunge zvikumbaridzo zvekuvimba zvikatariswa.
Implementation Roadmap
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa.
Tsanangura maitiro ekugamuchirwa echokwadi, kurangarira, uye mutengo wekukanganisa. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira.
Edzai nedata rinoenderana nemamiriro chaiwo ekugadzira. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura.
Wedzera ongororo yemunhu kune yakaderera-kusavimbika kana yakakwirira-inokanganisa kufanotaura. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset.
Tevera modhi kudonha uye simbisa mushure mekuchinja kwekamera kana dataset. Bata nhanho yega yega segedhi rehumbowo: kana maitiro asina kusangana, imbomira kuburitsa, vhara gaka, uye wobva wawedzera kushandiswa.