{"id":105302,"date":"2022-10-13T15:36:48","date_gmt":"2022-10-13T13:36:48","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/otkryt-kod-sistemy-mashinnogo-obucheniya-dlya-generaczii-realistichnyh-dvizhenij-cheloveka"},"modified":"2022-10-13T15:36:48","modified_gmt":"2022-10-13T13:36:48","slug":"otkryt-kod-sistemy-mashinnogo-obucheniya-dlya-generaczii-realistichnyh-dvizhenij-cheloveka","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sk\/blog\/news\/otkryt-kod-sistemy-mashinnogo-obucheniya-dlya-generaczii-realistichnyh-dvizhenij-cheloveka","title":{"rendered":"Odobrat\u00fd k\u00f3d syst\u00e9mu strojov\u00e9ho u\u010denia na generovanie realistick\u00fdch pohybov \u010dloveka","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Skupina v\u00fdskumn\u00edkov z Telavivskej univerzity odhalila zdrojov\u00e9 k\u00f3dy spojen\u00e9 so syst\u00e9mom strojov\u00e9ho u\u010denia MDM (Motion Diffusion Model), ktor\u00fd umo\u017e\u0148uje generova\u0165 realistick\u00e9 pohyby \u010dloveka. K\u00f3d je nap\u00edsan\u00fd v jazyku Python s vyu\u017eit\u00edm r\u00e1mca PyTorch a je distribuovan\u00fd pod licenciou MIT. Na vykon\u00e1vanie experimentov je mo\u017en\u00e9 pou\u017ei\u0165 ako hotov\u00e9 modely, tak aj tr\u00e9ning modelov samostatne pomocou navrhovan\u00fdch skriptov, napr\u00edklad pou\u017eit\u00edm zbierky trojrozmern\u00fdch obr\u00e1zkov \u010dloveka HumanML3D. Na tr\u00e9ning syst\u00e9mu je potrebn\u00e1 GPU s podporou CUDA. <\/p>\n

Pou\u017eitie tradi\u010dn\u00fdch mo\u017enost\u00ed na animovanie pohybov \u010dloveka je s\u0165a\u017een\u00e9 komplik\u00e1ciami spojen\u00fdmi s ve\u013ekou rozmanitos\u0165ou mo\u017en\u00fdch pohybov a \u0165a\u017ekos\u0165ou ich form\u00e1lneho popisu, ako aj so zna\u010dnou citlivos\u0165ou \u013eudsk\u00e9ho vn\u00edmania na neprirodzen\u00e9 pohyby. Predch\u00e1dzaj\u00face pokusy o vyu\u017eitie generat\u00edvnych modelov strojov\u00e9ho u\u010denia mali probl\u00e9my so kvalitou a obmedzenou v\u00fdraznos\u0165ou. <\/p>\n

V navrhnutom syst\u00e9me bola podniknut\u00e1 snaha o vyu\u017eitie dif\u00faznych modelov na generovanie pohybov, ktor\u00e9 s\u00fa svojou podstatou lep\u0161ie prisp\u00f4soben\u00e9 na simul\u00e1ciu \u013eudsk\u00fdch pohybov, no nie s\u00fa osloboden\u00e9 od nedostatkov, ako s\u00fa vysok\u00e9 n\u00e1roky na v\u00fdpo\u010dtov\u00e9 zdroje a zlo\u017eitosti riadenia. Na minimaliz\u00e1ciu nedostatkov dif\u00faznych modelov je v MDM zapojen\u00e1 neur\u00f3nov\u00e1 sie\u0165 s architekt\u00farou \u201etransform\u00e1tor\u201c a predikcia vzorky (sample) namiesto predikcie \u0161umu v ka\u017edom kroku, \u010do u\u013eah\u010duje predch\u00e1dzanie anom\u00e1li\u00e1m, ako je strata kontaktu povrchu s nohou. <\/p>\n

Na riadenie gener\u00e1cie to umo\u017e\u0148uje aplik\u00e1ciu textov\u00e9ho opisu akcie v prirodzenom jazyku (napr\u00edklad \u201e\u010dlovek ide dopredu a skl\u00e1n\u00ed sa, aby zdvihol nie\u010do zo zeme\u201c) alebo pou\u017eitie typov\u00fdch akci\u00ed, ako s\u00fa \u201ebeh\u201c a \u201eskoky\u201c. Syst\u00e9m je tie\u017e mo\u017en\u00e9 pou\u017ei\u0165 na \u00fapravu pohybov a doplnenie straten\u00fdch detailov. V\u00fdskumn\u00edci vykonali testovanie, ktor\u00e9ho \u00fa\u010dastn\u00edkom bolo pon\u00faknut\u00e9 vybra\u0165 si z nieko\u013ek\u00fdch mo\u017enost\u00ed kvalitnej\u0161\u00ed v\u00fdsledok \u2014 v 42% pr\u00edpadov \u013eudia dali prednos\u0165 syntetizovan\u00fdm pohybom pred skuto\u010dn\u00fdmi.

\r\n \"Prehrajte\r\n
<\/div>\r\n <\/div><\/center>
\n
Zdroj: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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