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• W2398346323 abstract "Recent progress in video description has shown promising results by combining object/action recognition and natural language processing techniques. However, even the most simplest form of the generated sentence, the SVO triplet (Subject/Verb/Object), can be misleading for its lack of role relationship analysis. When the system detects keywords person, and feed, we do not want the system to generate person feeding a when the actual screen is a scene where the baby is trying to share the food. In this paper, we explore role relationships between objects/persons and their usage in generating a more meaningful video description. More specifically, we confine ourselves on the following problem: identifying subject and object roles in two-person activities. We argue that the subject and object roles have consistent properties across different activities. To that end, we cast this problem as a domain adaptation problem. A novel Youtube SVO dataset is proposed for evaluating methods developed for this problem. The performance of the proposed method is compared against several baseline methods." @default.
• W2398346323 created "2016-06-24" @default.
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• W2398346323 date "2016-03-01" @default.
• W2398346323 modified "2023-09-23" @default.
• W2398346323 title "Is alice chasing or being chased?: Determining subject and object of activities in videos" @default.
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• W2398346323 doi "https://doi.org/10.1109/wacv.2016.7477710" @default.
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