16 citations · 65 across the 10 of their papers we have counts for
6 papers · 1 filter
Perspectives and Prospects on Transformer Architecture for Cross-Modal Tasks with Language and Vision
Andrew Shin, Masato Ishii, Takuya Narihira
Transformer architectures have brought about fundamental changes to computational linguistic field, which had been dominated by recurrent neural networks for many years. Its succes…
Reference-Based Video Colorization with Spatiotemporal Correspondence
Naofumi Akimoto, Akio Hayakawa, Andrew Shin +1
We propose a novel reference-based video colorization framework with spatiotemporal correspondence. Reference-based methods colorize grayscale frames referencing a user input color…
The Color of the Cat is Gray: 1 Million Full-Sentences Visual Question Answering (FSVQA)
Andrew Shin, Yoshitaka Ushiku, Tatsuya Harada
Visual Question Answering (VQA) task has showcased a new stage of interaction between language and vision, two of the most pivotal components of artificial intelligence. However, i…
DualNet: Domain-Invariant Network for Visual Question Answering
Kuniaki Saito, Andrew Shin, Yoshitaka Ushiku +1
Visual question answering (VQA) task not only bridges the gap between images and language, but also requires that specific contents within the image are understood as indicated by…
Beyond Caption To Narrative: Video Captioning With Multiple Sentences
Andrew Shin, Katsunori Ohnishi, Tatsuya Harada
Recent advances in image captioning task have led to increasing interests in video captioning task. However, most works on video captioning are focused on generating single input o…
Dense Image Representation with Spatial Pyramid VLAD Coding of CNN for Locally Robust Captioning
Andrew Shin, Masataka Yamaguchi, Katsunori Ohnishi +1
The workflow of extracting features from images using convolutional neural networks (CNN) and generating captions with recurrent neural networks (RNN) has become a de-facto standar…