Progressive Attention Memory Network for Movie Story Question Answering

This paper proposes the progressive attention memory network (PAMN) for movie story question answering (QA). Movie story QA is challenging compared to VQA in two aspects: (1) pinpointing the temporal parts relevant to answer the question is difficult as the movies are typically longer than an hour, (2) it has both video and subtitle where different questions require different modality to infer the answer... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Video Story QA MovieQA PAMN Accuracy 42.53 # 1

Methods used in the Paper


METHOD TYPE
Memory Network
Working Memory Models