5 citations · 7 across the 4 of their papers we have counts for
6 papers
DramaQA: Character-Centered Video Story Understanding with Hierarchical QA
Seongho Choi, Kyoung-Woon On, Yu-Jung Heo +4
Despite recent progress on computer vision and natural language processing, developing a machine that can understand video story is still hard to achieve due to the intrinsic diffi…
Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data
Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo +1
Conventional sequential learning methods such as Recurrent Neural Networks (RNNs) focus on interactions between consecutive inputs, i.e. first-order Markovian dependency. However,…
Compositional Structure Learning for Sequential Video Data
Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo +1
Conventional sequential learning methods such as Recurrent Neural Networks (RNNs) focus on interactions between consecutive inputs, i.e. first-order Markovian dependency. However,…
Constructing Hierarchical Q&A Datasets for Video Story Understanding
Yu-Jung Heo, Kyoung-Woon On, Seongho Choi +5
Video understanding is emerging as a new paradigm for studying human-like AI. Question-and-Answering (Q&A) is used as a general benchmark to measure the level of intelligence for v…
Visualizing Semantic Structures of Sequential Data by Learning Temporal Dependencies
Kyoung-Woon On, Eun-Sol Kim, Yu-Jung Heo +1
While conventional methods for sequential learning focus on interaction between consecutive inputs, we suggest a new method which captures composite semantic flows with variable-le…
Answerer in Questioner's Mind: Information Theoretic Approach to Goal-Oriented Visual Dialog
Sang-Woo Lee, Yu-Jung Heo, Byoung-Tak Zhang
Goal-oriented dialog has been given attention due to its numerous applications in artificial intelligence. Goal-oriented dialogue tasks occur when a questioner asks an action-orien…