UnconstrainedFaceAlignmentviaCascadedCompositionalLearning_ComposItionalLearning资源-CSDN文库

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CCL

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Unconstrained Face Alignment via Cascaded Compositional

Learning

摘要

󰟢󰦡实󳰖󱱕󰮊󱊦解󰐖󰮱󲑷󰴰󱱕󲜉󰇊󴔡󳮿󳹩󰟢󱱕󰮱󲑷󰴰󳮿󳹩󰟢

󳳑要理󱱕󳚹󰗒󰆝󱱕󰔳󱢇󰔳󰓦󳍈󱱕󱱕󰔳󱢇󲸹󲾓󱱕󲛎󰮱󲑷󰴰󱱕

󰱀󰟢󱱕级联󰔣󲛎理󰈑󰔳󱢇󲾕󱱕󲸹󲾓 - 󰔳󱢇关󲋌󰟢󰇗󲁋󳯅

󱾞󲉌󱱕󰇗󱡊󰅫󱱕󰔣󳅲󱱕组合作󳹕󱌜󱱕󰔳󱢇󳗫󳖘󱫹󱡊󰅫󲸹󱼋󱱕学

习󱲿󰷘󰭁󰮁󱱕󰷢󲺓󰭁󰟢󱱕󰮊󱊦󲛎󳅲󴉒󰺣󰗸󱱕󰑇󰳚󰛠󱱕组合󱬂

󱫹󰖼󳗰󱱕󰥣󳰵󰴋󱫹󰖼󳗰󱱕󲋱󱡊󰕒󰟢󱱕󰮊󱊦󱱕󳗰󰑷󲛎󳖏 300FPS󰑇

󲊏󰑷󳍖󳖘󱦁󰳚󱱕󰮊󱊦

1 简介

󰳽󰭘󰟢󰦡󰳚󰬙󱱕󰑇󴂩󰬙󱱕󰮱󲑷󰴰󱱕󲜉󰇊󴔡󰮊󱊦󰅔󳌧 3D 󲜉󰿲

 3D 󱊹󳞛󱉲󰳚󰅫󳚹󰗒󱱕󲣔󰅔󲛎󰕙󰆊󰯤󱱕理󰭅 AFLW 󰭁󰤿󳲗󱱕󰛠󱱕󲾣

󰑷󰆝󱱕󲸹󰚖󱄵󰇊󴔡󳳑要󰓱󳖬󲸝󲗝󳳑要󰯇󳯅验󰟢󰇗󲒪󳖪

󰓦󱱕󰈯󰗸󳗫󳖘󰇗󱌒󲸝󱱕级联󰔣󲄧󱬶󲸹󱼋级联󱱕组合学习 (cascaded compositional

learning,CCL) 󳮿󳹩󰴶󰅝󰟡󱡊󰟢󱫹级联󰔣󰴶󲽗󱲧󰈑󰔳󱢇󰭁󲁋󳯅󰭘󱣿

[37] 󰸈󰟢󰇗󰳑󲁋󳯅󰟡󱾞󲉌󱱕󳩙󰇊󱆠󱫹󱡊󰅫󱱕级联󰔣

󲒪󰅫󰐖󱌜󳆦󰅔󱱕󰔳󱢇󳅲󱾞 DHDsdomains of homogeneous descent󱱕组合󰔳

󱢇󰟢󰔋󳇔 CCL 󰢶󰳚󱱕󱱕󰈯󰗸

(i)

󴉒󰺣󰗸󱱕组合󳹕󱌜

:󰟢󱫹󰮁󱱕󲺓󰭁󲄧󰷢󰸗󰶇󳅲组合󱶳󳞠󰭁

󱱕󲸹󱼋󱒲󳎄󱳅󰥶󰳑󱚊󱱕󲔿󱄵󲒪󰅫󰛠󱱕󰗒󲜉󰔳󱫰󲊏󱸿

󱱕󰇊󴔡󰵭󰭁󱱕󳆮󳴳󰟢󱳜󰇠󱱕󰔳󱢇󰭁󳇀󰎿󰑇󰇊󰑥󰇠󱱕󱚊󰅫󳇀

󰎿󰟢󱊹󰛠󳖪󰰀󰕙󱳰󱱕󱏈合󳅲󰟢󳳑要󱸿󳖪󰻆󰷢󲛎󳅲󰳚󰛠󱱕组合

󳆶组合󰤦󰤚󳯅󱱕相关󰗸󱄵󳅲󱱕组合󱶳󳞠󳆾󳆉󰳅相󳚌󱱕相󱱕󰥹󲤡

󲗝󰰀󲁋󳯅󱱕󳖭󱾌󱱕(ii) 󰖼󳗰󰟢󰇗󰮊󱊦󲸹󱼋实󰯇󱱕󰓔󰮱󰏝󰳬󱱕󱄵󳆶󰮊󱊦󱫹

󰖼󳗰󱱕󲋱󰎿󱡊󰕒 [5]

xuluhui123@126.com

 1 󱾞󰮊󱊦 AFLW 󰭁󰤿󳲗󱱕󱌜󳆦󳇀󰎿󰏔󰟢󳗚󰢺󲋱Yaw 󲾣󱱕󰇠󲾗󰏔󰑇󰦡 5 

 (I,V) 󰳚󲸹󰗸󱱕󲜉󳗫󳖘󲾓󰆰󱳜级联󰔣󰮊󱊦󲜉󲦈󰕨󰇠󱱕󳇀󰎿󲾗󲾣󱱕󰮊󱊦

󲛎󳴳󱱕解󰈑󰔳󱢇󲸹󲾓󰟢󱱕级联组合󱱕学习󰠑󰳚󲜉󱫰󱒲󰛠󱱕󲒤󰵭.

2 相关工作

Jourabloo 󲄚 [18] 󰦡 3D 󰮊󱊦󱫹级联󰔣󳹕󱌜 3D 󰔳󱢇󱱕󲋌󰭁 3D-2D 󱱕

󰡦󰕂󱶺󳰆󰟢实验󰅵󲸹󰯟󰳑󰔳󱢇󲋌󰭁󰡦󰕂󰰀󳯅󰥶󱱕󰑇󰰀󱃲󱱕󰳅󰇠󱱕

󰭁󳇀󰎿󰑇󰅫󲄚󰳅󰇠󱱕󰇊󴔡󳇀󰎿 [5]Tulyakov 󲄚󰇗󰔣󱲿󰷘󰠺󰈦 3D 󲁋󳯅󱜇󲗝󳖪

󰮊󱊦󳌧󰳚󰔳󱢇󳰡󱱕 3D 󰭁󰤿󳲗󰑇󲛎󱫹󱦁󰳚󱱕 2D 󲞻󱜇󰱀󱱕󰭁󰤿󳲗

AFLW  20K+ 󰭁󰤿󳲗Wu[34] 󲄚󰦡󳘿󰣲󴉒󰺣󱱕级联󰔣󰮊󱊦󰴶理󰵒󲃀󱱕󰗒󳘿

󰣲󰰀󰅔󱱕󰮊󱊦󰇢󳞠󱱕实验󰅵󱦀󱱕󰣢󰟩󳖬󲸝验󳆒󲔋󱡊󰅫󱱕󰴋󰴶理

󰛠󰔳󱢇󲗝󰰀󱾞󰷘󱱕󳴳󲾗󲾣Hsu 󲄚 [17] 󰠺󰈦󱏈合󰷢󰿲 [45]󰑇󳖏󰳅

󱱕󲊏󰑷󰬙󱥘󱜇󲗝󰰀󰅫󲜉󰔳󱢇󰰀󰷢󲒤󰵕󰔳󱢇󰮎󰔋󱱕󲑷󰴰

3 级联组合学习

󲒪󰅫󲜉 I󲜉󰔳󱢇󰇊󴔡󲅨󱊦󱱕󱲿󰷘󰰀󳹕󱌜󲜉󰔳󱢇 S. 󰈂󰰀 L 󱚊󱱕 x, y 

󰷘 [x

, y

, ..., x

, y

, ..., x

, y

] 级联󰔣󰮊󱊦 ( [36,27]  T 󱃲󳖾󱆠󱃲󳖾󳖘󱿜󳗫󳖘󳴳󱱕

󰔳󰓠󰳅󰮁󰔳󱢇:

= S

t−1

+ W

Φ(I; S

t−1

) (1)

学习󱱕󲒐󰗸󰔣 W

󱫹󰇗󰔳󱢇󲋳󰓦󱡊󰕒 ϕ

(I, S

t−1

) 󰯱󰇕󰔳󱢇󱅜󰎿

解󰔤󰈑󳚹󰔣󰑥󱫹󱱕󰈑󰤳󱱕󰔳󱢇󰯇󰈑󳚹󰔣󱱕󳰡󰟢󰦡󰇗󱆠󱃲󳖾

󱱕󰔳󱢇󳹕󱌜󲸹󱼋 DHDs 󱱕󰔳󱢇󳅲󱱕组合󰳅󲊏󱸿󱱕󲸹󱼋󰟢󰅫组󱡊󰅫

󰈑󳚹 -󳰞󰔣 W

= w

, ..., w

组合󳅲 f

󰟢󱃲级联󳗫󳖘󳴳󱱕

󰓠󳹕󱌜󰔳󱢇

∑

k=1

, s

= S

t−1

+ △s

(2)

△s

= w

(I; S

t−1

), p

= f

(Φ

′

(I; s

k=1...K

)) (3)

󱆠󱱕󳰞 △s

组合󱶳󳞠 p

= [p

, ..., p

]

󳛎󰰀󰔳󱢇󲋳󰓦󱡊󰕒󱱕󳅲󲄚

󰓠3󲃽3.1󳖬󲸝󳆷󲒗󱱕󰦠󳗁). 󱄵组合 p

󰰀󰳚󰛠󱱕󰅫󰗸󱱕󱱕󰦠󳗁󰆊

󱱕󰎷󲾗󲾣󲾗󲾣󱱕组合󲛎󰯇󱫰. 󱆠组合󰰀󳴯󳋰󱱕󰦡󰳚󰬙󱱕󰔳󱢇󳋲

󱣿󰟢󰣘组合 p

󰰀 △s

󳖬󲸝󳅲󱱕󱄵󰅔󱳅󰥶󱫹󰈑󳚹󲸹󲾓󱡊󰕒 Φ

′t

(I; s

)

󱄵󰮱󲑷󰴰󱱕󰱀󰟢󱱕󰮊󱊦󰢎

󰖼󳗰󲋱󱡊󰕒

(fast pixel feature) 󳖬󲸝󱚊󱱕󰺑

󱌜

. 󰟢󳗫󳖘󰇗󰠑󰳚󱱕󳅾󲒔󰸈󰳽 K 󰄡󳲗󰴶󰅫 K 󳞘󱫹󰭘󱣿 [37] 󰮊󱊦󰟢󰸊󰤿

󰔳󱢇󰈑󳚹󲸹󲾓󱱕󰟡󰴶󰠑󰳚󱱕󰸈󰳽󱆠󰟡󰇗󰸈󰳽󰟡󱄵K 󰘌󰰀 2 󱱕󰐓󱃲

󰮊󰕨󳇅󰯟󱱕󰰀󳚹󰗒󰰀󱱕󱔭󲋱󳗫󳖘󲾓󰆰󱆠󱱕󰑄󲜉󰟢󱦁

󱬂󰔳󰟧󲗖󲸹󲾓󰈯󰗸󰇍󰅝󰓱󰓑󱱕󱱕󳴳󳚹󲓺󰬏󱱕󲜉󳔿󰒤󰟧󲗖󰏷󰳚

󳬭󱱕󲜉󰠑󰳚󱱕󰸈󱱕󱡊󰕒󰯱󰇕 (Φ

)󰓠3󱈓解 △s

󰇊󱱕 (󱱕 k 󳞘

󱫹相󱱕 Φ

󰥹󰭾. 2󳯡󳗁 CCL 󱌜󳆦󳰇󱆆󱱕󱃲󳖾󰟢󳽧󳖾󱱕󰔳󱢇󳅲󲦈󰕨󰔳󱢇󲋳󰓦󱡊

󰕒󰥶󱴑󰇗󳆶󱡊󰕒󳗒󰠑󰳚󰴶󲦈󰕨󱱕󳅲󱱕󰔳󱢇󱅜󰎿相󰑥󱱕󰳅󰮁󲔿󱱕󲋳󰓦󱡊

󰕒󱜇󰟢󳗫󳖘联合󱱕󲗔󲰢󰠑󰳚󱱕󰈑󳚹󲸹󲾓󰴶󳹕󱌜󱱕组合󰟢󳞞󳴳󱱕󳖘󱿜 T(󲄚

󰓠2,3) 󱃲󲦈󰕨󰟢󰳑󲒙󱱕󳅲. 󱊹󰛠󲃽󱃲󳖾󱉲󰳚 S

t−1

󱄵󱆠󱡊󰅫󱱕󰑄󰔳󱢇󰓑

󳖬󱄶󱱕󳗰󰟢󳗓󰔤󱱕实󰯇󱱕󰥣󳰵󰆊󱱕󰈂2󰈦󱼋󱱕󰵭 k 󰇊󰑥󱱕

组合󳅲󰰀 0 󰈂󰰀󳇅 p

= 0). 󰟢󲂜󰥣󳰵󳖪󰑇󲒦󳖘󰅔󱱕󳅲󲅨󰟢󲒠验󱦁

󳖪󲄧󱬶󳗰󰥹󰭾󱱕󳖘󱿜4 󱉲󰳚󲊏󰑷󱱕󰤰

 2 󳯡󳗁级联组合学习 (CCL) 󱱕󱃲󳖾󰅔󰢽󱄶󴁵:1) 󴉒󰺣󱱕󱡊󰕒󰯱󰇕󲦈󰕨󰔳󱢇󲋳󰓦󱡊󰕒 Φ

(I; S

t−1

);2) 󱆠

󲦈󰕨󰔣󰔳󱢇 s

相󰑥󱱕󱡊󰕒 Φ

′t

(I; s

)3) 󳹕󱌜组合 p

󲦈󰕨󳅲󱱕󰔳󱢇 S

󱄵󰟢󱱕󰿲󱆠󱃲󳖾󰢽󰟡

󱡊󰕒󱱕󰦡 Φ

, 组󰈑󳚹󰔣 W

= w

, ..., w

组合󳅲 f

. 󱫹实󰯇󱱕󱱕󰥣󳰵󰴋󱄶󴁵 2 

󰵭󲃽 k 󳖾󰏃󲒠󲹼󰥣󳰵󳙴󰟢󲒦󳖘 s

 Φ

(I; s

) 󱱕󳅲󲅨󲃽 k 󰥣󳰵s

 Φ

(I; s

) 󱱕󰣒

󰅫

学习󰟢󳖯󲒾󱱕学习󰔳󱢇󰯱󰇕 Φ

组合󰔳󱢇󳅲 (W

, p

)󰅔󱱕󰴋学习󱄶󴁵󳛎󲃽3.1

3.2󳆷󲒗󱱕󰦠󳗁󳅹󳆋󰟢󰸗󰶇󱱕󰸉󰖔󱄶󴁵󰟢󳗫󳖘󰓦组合󰔳󱢇 (W

, p

) 󱱕学习󰓑

󰟢󰇗󳚹3.2󰈦󱼋󱡊󰕒 Φ

′

󰰀 Φ 󱱕󱾞󰳅󱱕󱫹󰥹󰭾组合 p

评论收藏

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z117519

2017-02-08

这篇论文的效果很高不知如何实现
xiejin392025787

2017-06-19

刚准备看原文，结果找到了相关中文理解文档，赞！

机器学习的小学生

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