Top > ã¨ã³ã¸ãã¢ãªã³ã° > AIãä¸è¬äººãä¸ç¬ã§ãã³ãµã¼ã«ãOpenPoseãå¿ç¨ãããEverybody Dance Nowããããã
Top > ã¨ã³ã¸ãã¢ãªã³ã° > AIãä¸è¬äººãä¸ç¬ã§ãã³ãµã¼ã«ãOpenPoseãå¿ç¨ãããEverybody Dance Nowããããã
ABEJAã§ãªãµã¼ãã£ã¼ããã¦ãã¾ãé«æ©ã§ãã æ¨ä» deep learning çéã§ã¯ Generative Adversarial Net(GAN) ãæµè¡ã£ã¦ãã¦ãä¸ã¯ã¾ãã«ã¬ã³ã¬ã³è¡ãããæ代ã§ããã GAN ãç¨ããã¨ç¶ºéºãªçµµãä½æã§ãããäºã¤ã®çµµã®ä¸éã®ãããªçµµãçæã§ããããã¾ããä¾ãã°ãã®è«æã®ãããªæãã§ãããã®ããã« GAN ã¯æç¨ãªã¢ãã«ã§ããä¸æ¹ãæè¿ã® GAN ã§ã¯æ¥ã«ããããããªãå¼ãåºã¦ãããããã®ã§ãåå¼·ãå ¼ãã¦ãä¸æ¥ä¸GANãããã£ã¦ã¿ã¾ãããä»åèªãã è«æã®ãªã¹ãã¯ä»¥ä¸ã§ãã EBGAN (https://arxiv.org/abs/1609.03126 ) WGAN (https://arxiv.org/abs/1701.07875) LSGAN (https://arxiv.org/abs/1611.04076) f-GAN (https://ar
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