{"id":85284,"date":"2020-06-14T19:42:01","date_gmt":"2020-06-14T17:42:01","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/pifu-sistema-mashinnogo-obucheniya-dlya-postroeniya-3d-modeli-cheloveka-na-osnove-2d-snimkov"},"modified":"2020-06-14T19:42:01","modified_gmt":"2020-06-14T17:42:01","slug":"pifu-sistema-mashinnogo-obucheniya-dlya-postroeniya-3d-modeli-cheloveka-na-osnove-2d-snimkov","status":"publish","type":"post","link":"https:\/\/prohoster.info\/it\/blog\/novosti-interneta\/pifu-sistema-mashinnogo-obucheniya-dlya-postroeniya-3d-modeli-cheloveka-na-osnove-2d-snimkov","title":{"rendered":"PIFu \u2014 un sistema di machine learning per la creazione di un modello 3D di una persona a partire da immagini 2D","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Un gruppo di ricercatori di diverse universit\u00e0 americane ha pubblicato un progetto PIFu<\/a><\/noindex> (Pixel-Aligned Implicit Function), che consente di applicare metodi di apprendimento automatico per costruire un modello 3D di una persona a partire da una o pi\u00f9 immagini bidimensionali. Il sistema \u00e8 in grado di ricreare varianti complesse di abbigliamento, come gonne plissettate e scarpe con tacco, e diverse acconciature, ripristinando autonomamente la texture e la forma in aree invisibili nella proiezione da cui viene realizzato il modello 3D. Per aumentare la qualit\u00e0 e il dettaglio del modello 3D finale, possono essere utilizzate pi\u00f9 immagini da angolazioni diverse. Il codice del progetto \u00e8 scritto in Python utilizzando il framework PyTorch e distribuito<\/a><\/noindex> sotto licenza MIT.<\/p>\n

\"PIFu<\/a><\/noindex><\/center><\/p>\n

Per la ricostruzione di un modello volumetrico si utilizza una rete neurale che permette di scegliere la forma pi\u00f9 probabile e di completare gli elementi nascosti, basandosi su un modello addestrato su diverse varianti di oggetti esistenti. Parallelamente, il progetto fornisce un algoritmo per allineare il modello volumetrico ottenuto con le texture sulle immagini bidimensionali fornite, che allinea i pixel dell'immagine 2D secondo la loro posizione sull'oggetto 3D e genera le texture mancanti pi\u00f9 probabili. Qualsiasi rete neurale convoluzionale<\/a><\/noindex>, per
\nper la ricostruzione della superficie \u00e8 stata applicata l'architettura \u00abStacked hourglass<\/a><\/noindex>\u00bb, a
\n per il confronto delle texture \u00e8 stata utilizzata una rete neurale basata sull'architettura CycleGAN<\/a><\/noindex>.<\/p>\n

\"PIFu<\/a><\/noindex><\/center><\/p>\n

Il modello pre-addestrato utilizzato dai ricercatori \u00e8 disponibile<\/a><\/noindex> \u00e8 disponibile per il download gratuito, ma i dati originali su cui \u00e8 stato effettuato l'addestramento rimangono riservati, poich\u00e9 si basano su risultati di scansioni 3D commerciali. Come fonte per l'auto-addestramento del modello pu\u00f2 essere utilizzata una banca di modelli 3D<\/a><\/noindex> persone dal progetto Renderpeople.<\/p>\n

\r\n \"Riproduci\r\n
<\/div>\r\n <\/div><\/center><\/p>\n

<\/a><\/noindex><\/p>\n

Fonte: opennet.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u0413\u0440\u0443\u043f\u043f\u0430 \u0438\u0441\u0441\u043b\u0435\u0434\u043e\u0432\u0430\u0442\u0435\u043b\u0435\u0439 \u0438\u0437 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u0445 \u0430\u043c\u0435\u0440\u0438\u043a\u0430\u043d\u0441\u043a\u0438\u0445 \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442\u043e\u0432 \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043b\u0430 \u043f\u0440\u043e\u0435\u043a\u0442 PIFu (Pixel-Aligned Implicit Function), \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u044e\u0449\u0438\u0439 \u043f\u0440\u0438\u043c\u0435\u043d\u0438\u0442\u044c \u043c\u0435\u0442\u043e\u0434\u044b \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0434\u043b\u044f \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f 3D-\u043c\u043e\u0434\u0435\u043b\u0438 \u0447\u0435\u043b\u043e\u0432\u0435\u043a\u0430 \u043f\u043e \u043e\u0434\u043d\u043e\u043c\u0443 \u0438\u043b\u0438 \u043d\u0435\u0441\u043a\u043e\u043b\u044c\u043a\u0438\u043c \u0434\u0432\u0443\u043c\u0435\u0440\u043d\u044b\u043c \u0438\u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u0438\u044f\u043c. \u0421\u0438\u0441\u0442\u0435\u043c\u0430 \u043f\u043e\u0437\u0432\u043e\u043b\u044f\u0435\u0442 \u0432\u043e\u0441\u0441\u043e\u0437\u0434\u0430\u0432\u0430\u0442\u044c \u0441\u043b\u043e\u0436\u043d\u044b\u0435 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u044b \u043e\u0434\u0435\u0436\u0434\u044b, \u0442\u0430\u043a\u0438\u0435 \u043a\u0430\u043a \u044e\u0431\u043a\u0438 \u0441\u043e \u0441\u043a\u043b\u0430\u0434\u043a\u0430\u043c\u0438 \u0438 \u0442\u0443\u0444\u043b\u0438 \u043d\u0430 \u043a\u0430\u0431\u043b\u0443\u043a\u0430\u0445, \u0438 \u0440\u0430\u0437\u043b\u0438\u0447\u043d\u044b\u0435 \u043f\u0440\u0438\u0447\u0451\u0441\u043a\u0438, \u0441\u0430\u043c\u043e\u0441\u0442\u043e\u044f\u0442\u0435\u043b\u044c\u043d\u043e \u0432\u043e\u0441\u0441\u0442\u0430\u043d\u0430\u0432\u043b\u0438\u0432\u0430\u044f \u0442\u0435\u043a\u0441\u0442\u0443\u0440\u0443 \u0438 \u0444\u043e\u0440\u043c\u0443 \u0432 \u043e\u0431\u043b\u0430\u0441\u0442\u044f\u0445, \u043d\u0435\u0432\u0438\u0434\u0438\u043c\u044b\u0445 \u0432 \u043f\u0440\u043e\u0435\u043a\u0446\u0438\u0438, […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":85285,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-85284","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-novosti-interneta"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47PIFu \u2014 un sistema di apprendimento automatico per la creazione di un modello 3D di una persona basato su immagini 2D | ProHoster","description":"Un gruppo di ricercatori di diverse universit\u00e0 americane ha pubblicato il progetto PIFu (Pixel-Aligned Implicit Function), che consente di applicare metodi di apprendimento automatico per creare un modello 3D di una persona da una o pi\u00f9 immagini bidimensionali. Il sistema permette di ricreare complessi stili di abbigliamento, come gonne plissettate e tacchi alti, e diverse acconciature, ripristinando autonomamente la texture e la forma nelle aree invisibili nella proiezione.","canonical_url":"https:\/\/prohoster.info\/it\/blog\/novosti-interneta\/pifu-sistema-mashinnogo-obucheniya-dlya-postroeniya-3d-modeli-cheloveka-na-osnove-2d-snimkov","robots":"max-image-preview:large","keywords":"","webmasterTools":{"miscellaneous":""},"schema":null,"og:locale":"it_IT","og:site_name":"ProHoster | \u041a\u0443\u043f\u0438\u0442\u044c \u043d\u0430\u0434\u0435\u0436\u043d\u044b\u0439 \u0445\u043e\u0441\u0442\u0438\u043d\u0433 \u0434\u043b\u044f \u0441\u0430\u0439\u0442\u043e\u0432 \u0441 \u0437\u0430\u0449\u0438\u0442\u043e\u0439 \u043e\u0442 DDoS, VPS VDS \u0441\u0435\u0440\u0432\u0435\u0440\u044b","og:type":"article","og:title":"\ud83e\udd47PIFu \u2014 \u0441\u0438\u0441\u0442\u0435\u043c\u0430 \u043c\u0430\u0448\u0438\u043d\u043d\u043e\u0433\u043e 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