5 citations · 5 across the 4 of their papers we have counts for
6 papers
Learning by Asking Questions for Knowledge-based Novel Object Recognition
Kohei Uehara, Tatsuya Harada
In real-world object recognition, there are numerous object classes to be recognized. Conventional image recognition based on supervised learning can only recognize object classes…
K-VQG: Knowledge-aware Visual Question Generation for Common-sense Acquisition
Kohei Uehara, Tatsuya Harada
Visual Question Generation (VQG) is a task to generate questions from images. When humans ask questions about an image, their goal is often to acquire some new knowledge. However,…
ViNTER: Image Narrative Generation with Emotion-Arc-Aware Transformer
Kohei Uehara, Yusuke Mori, Yusuke Mukuta +1
Image narrative generation is a task to create a story from an image with a subjective viewpoint. Given the importance of the subjective feelings of writers, readers, and character…
Unsupervised Keyword Extraction for Full-sentence VQA
Kohei Uehara, Tatsuya Harada
In the majority of the existing Visual Question Answering (VQA) research, the answers consist of short, often single words, as per instructions given to the annotators during datas…
Interactive Video Retrieval with Dialog
Sho Maeoki, Kohei Uehara, Tatsuya Harada
Now that everyone can easily record videos, the quantity of which is continuously increasing, research on methods for improved video retrieval is important in the contemporary worl…
Visual Question Generation for Class Acquisition of Unknown Objects
Kohei Uehara, Antonio Tejero-De-Pablos, Yoshitaka Ushiku +1
Traditional image recognition methods only consider objects belonging to already learned classes. However, since training a recognition model with every object class in the world i…