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[๋…ผ๋ฌธ ์†Œ๊ฐœ] Drag Your GAN - ๋งˆ์šฐ์Šค ๋“œ๋ž˜๊ทธ๋กœ ์ด๋ฏธ์ง€๋ฅผ ์ƒ์„ฑ/๋ณ€ํ˜•ํ•˜๋Š” AI

by ๋ญ…์ฆค 2023. 5. 28.
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Drag Your GAN

 

 

์ด์ „์˜ ์ ‘๊ทผ ๋ฐฉ์‹๊ณผ ๋‹ฌ๋ฆฌ Drag Your GAN์€ ์‚ฌ์šฉ์ž์˜ ๋งˆ์šฐ์Šค ๋“œ๋ž˜๊ทธ๋งŒ์œผ๋กœ GAN์„ ์ œ์–ดํ•œ๋‹ค. ๋…ผ๋ฌธ ์ €์ž๋Š” ๋ˆ„๊ตฌ๋‚˜ ํ”ฝ์…€์˜ ์œ„์น˜๋ฅผ ์ •๋ฐ€ํ•˜๊ฒŒ ์ œ์–ดํ•˜์—ฌ ์ด๋ฏธ์ง€๋ฅผ ๋ณ€ํ˜•ํ•  ์ˆ˜ ์žˆ์œผ๋ฏ€๋กœ ๋™๋ฌผ, ์ž๋™์ฐจ, ์ธ๊ฐ„, ํ’๊ฒฝ ๋“ฑ๊ณผ ๊ฐ™์€ ๋‹ค์–‘ํ•œ ๋ฒ”์ฃผ์˜ ํฌ์ฆˆ, ๋ชจ์–‘, ํ‘œํ˜„ ๋ฐ ๋ ˆ์ด์•„์›ƒ์„ ์กฐ์ž‘ํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ํ•œ๋‹ค. ๋…ผ๋ฌธ์— ๊ณต๊ฐœ๋œ figure๋ฅผ ๋ณด๋ฉด ์‚ฌ์ž์˜ ์ž…์„ ๋“œ๋ž˜๊ทธํ•˜์—ฌ ๋ฒŒ๋ฆฌ๊ฒŒ ํ•˜๊ฑฐ๋‚˜ ๋‹ค๋ฅธ ๊ณณ์„ ์‘์‹œํ•˜๊ฒŒ ํ• ์ˆ˜ ์žˆ๊ณ , ์‚ฌ๋žŒ์˜ ์ž์„ธ๋ฅผ ๋ฐ”๊พธ๊ฑฐ๋‚˜ ํ’๊ฒฝ ์† ์‚ฐ์˜ ๋†’์ด๋ฅผ ๋ฐ”๊ฟ€ ์ˆ˜๋„ ์žˆ๋‹ค. ๋ฌผ๋ก  ๊ฝค๋‚˜ ์ž์—ฐ์Šค๋Ÿฝ๊ฒŒ ๋ง์ด๋‹ค. GAN ๋ถ„์•ผ์—์„œ ์ด๋ฏธ ์ด๋ฏธ์ง€ ๋งค๋‹ˆํด๋“œ๋ฅผ ํ•™์Šตํ•˜์—ฌ ์ด๋ฏธ์ง€๋ฅผ ์ƒ์„ฑ/๋ณ€ํ˜•ํ•˜๋Š” ์—ฐ๊ตฌ๋Š” ๋งŽ์•˜์ง€๋งŒ ์ด๋ ‡๊ฒŒ ๋ญ”๊ฐ€ ํ”„๋กœ๋•ํŠธํ™”(?)๋˜์–ด ๊ณต๊ฐœ๋œ ๋…ผ๋ฌธ์€ ์ฒ˜์Œ ๋ณด๋Š” ๊ฒƒ ๊ฐ™๋‹ค.

 

Motion supervision ๋‹จ๊ณ„๋Š” ํ•ธ๋“ค ํฌ์ธํŠธ(๋นจ๊ฐ„์ƒ‰ ์ )๋ฅผ ๋“œ๋ผ์ด๋ธŒํ•˜์—ฌ ํƒ€๊ฒŸ ํฌ์ธํŠธ(ํŒŒ๋ž€์ƒ‰ ์ )๋ฅผ ํ–ฅํ•ด ์ด๋™ํ•˜๊ณ , point tracking ๋‹จ๊ณ„๋Š” ํ•ธ๋“ค ํฌ์ธํŠธ๋ฅผ ์—…๋ฐ์ดํŠธํ•˜์—ฌ ์ด๋ฏธ์ง€ ์† ๊ฐ์ฒด๋ฅผ ์ถ”์ ํ•œ๋‹ค๊ณ  ํ•œ๋‹ค. ์ด ํ”„๋กœ์„ธ์Šค๋Š” ํ•ธ๋“ค ํฌ์ธํŠธ๊ฐ€ ํƒ€๊ฒŸ ํฌ์ธํŠธ์— ๋„๋‹ฌํ•  ๋•Œ๊นŒ์ง€ ๊ณ„์†๋œ๋‹ค.

 

์ด๋Ÿฌํ•œ motion supervision์€ generator์˜ feature map์—์„œ ์‹œํ”„ํŠธ๋œ patch loss๋ฅผ ํ†ตํ•ด ๋‹ฌ์„ฑ๋˜๊ณ , nearest neighbor search ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด ๋™์ผํ•œ feature space์—์„œ point tracking์„ ์ˆ˜ํ–‰ํ•œ๋‹ค๊ณ  ํ•œ๋‹ค.

 

 


 

์•„๋ž˜์— ํ”„๋กœ์ ํŠธ ํŽ˜์ด์ง€์™€ ์˜ˆ์‹œ ์˜์ƒ์„ ์ฒจ๋ถ€ํ•œ๋‹ค.

 

Project Page

 

Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

--> Abstract Synthesizing visual content that meets users' needs often requires flexible and precise controllability of the pose, shape, expression, and layout of the generated objects. Existing approaches gain controllability of generative adversarial net

vcai.mpi-inf.mpg.de

 

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