51 citations · 141 across the 13 of their papers we have counts for
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Transferring Domain-Agnostic Knowledge in Video Question Answering
Tianran Wu, Noa Garcia, Mayu Otani +3
Video question answering (VideoQA) is designed to answer a given question based on a relevant video clip. The current available large-scale datasets have made it possible to formul…
A Picture May Be Worth a Hundred Words for Visual Question Answering
Yusuke Hirota, Noa Garcia, Mayu Otani +4
How far can we go with textual representations for understanding pictures? In image understanding, it is essential to use concise but detailed image representations. Deep visual fe…
Understanding the Role of Scene Graphs in Visual Question Answering
Vinay Damodaran, Sharanya Chakravarthy, Akshay Kumar +5
Visual Question Answering (VQA) is of tremendous interest to the research community with important applications such as aiding visually impaired users and image-based search. In th…
Constructing a Visual Relationship Authenticity Dataset
Chenhui Chu, Yuto Takebayashi, Mishra Vipul +1
A visual relationship denotes a relationship between two objects in an image, which can be represented as a triplet of (subject; predicate; object). Visual relationship detection i…
A Dataset and Baselines for Visual Question Answering on Art
Noa Garcia, Chentao Ye, Zihua Liu +5
Answering questions related to art pieces (paintings) is a difficult task, as it implies the understanding of not only the visual information that is shown in the picture, but also…
Knowledge-Based Visual Question Answering in Videos
Noa Garcia, Mayu Otani, Chenhui Chu +1
We propose a novel video understanding task by fusing knowledge-based and video question answering. First, we introduce KnowIT VQA, a video dataset with 24,282 human-generated ques…