Captioning Images with Novel Objects via Online Vocabulary Expansion

• URL: http://arxiv.org/abs/2003.03305v1
• Date: Fri, 6 Mar 2020 16:34:15 GMT
• Title: Captioning Images with Novel Objects via Online Vocabulary Expansion
• Authors: Mikihiro Tanaka, Tatsuya Harada
• Abstract summary: We introduce a low cost method for generating descriptions from images containing novel objects. We propose a method that can explain images with novel objects without retraining using the word embeddings of the objects estimated from only a small number of image features.
• Score: 62.525165808406626
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this study, we introduce a low cost method for generating descriptions from images containing novel objects. Generally, constructing a model, which can explain images with novel objects, is costly because of the following: (1) collecting a large amount of data for each category, and (2) retraining the entire system. If humans see a small number of novel objects, they are able to estimate their properties by associating their appearance with known objects. Accordingly, we propose a method that can explain images with novel objects without retraining using the word embeddings of the objects estimated from only a small number of image features of the objects. The method can be integrated with general image-captioning models. The experimental results show the effectiveness of our approach.

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