著者

笠井 誠斗 秋本 直郁 林 昌希 青木 義満

出版者

公益社団法人 精密工学会

雑誌

精密工学会誌 (ISSN:09120289)

巻号頁・発行日

vol.85, no.12, pp.1102-1109, 2019-12-05 (Released:2019-12-05)

参考文献数

15

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In this paper, a novel setting is tackled in which a neural network generates object images with transferred attributes, by conditioning on natural language commands. Conventional methods for object image transformation have used visual attributes, which are components that describe the object's color, posture, etc. This paper builds on this approach and finds an algorithm to precisely extract information from natural language commands, which transfers the attributes of an image and completes this image translation model. The effectiveness of our information extraction model is experimented, with additional tests to see if the change in visual attributes is correctly seen in the image.