Knowledge-driven description synthesis for floor plan interpretation
نویسندگان
چکیده
Image captioning is a widely known problem in the area of AI. Caption generation from floor plan images has applications indoor path planning, real estate, and providing architectural solutions. Several methods have been explored literature for generating captions or semi-structured descriptions images. Since only caption insufficient to capture fine-grained details, researchers also proposed descriptive paragraphs However, these rigid structure lack flexibility, making it difficult use them real-time scenarios. This paper offers two models, description synthesis image cue (DSIC) transformer-based (TBDG), text These models take advantage modern deep neural networks visual feature extraction generation. The difference between both way they input image. DSIC model takes features automatically extracted by network, while TBDG learns textual with paragraphs. specific keywords generated understanding make more robust general Experiments were carried out on large-scale publicly available dataset compared state-of-the-art techniques show model’s superiority.
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ژورنال
عنوان ژورنال: International Journal on Document Analysis and Recognition
سال: 2021
ISSN: ['1433-2833', '1433-2825']
DOI: https://doi.org/10.1007/s10032-021-00367-3