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231225s2018 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2018.2828437
|2 doi
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|a eng
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|a Das, Abhishek
|e verfasserin
|4 aut
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| 245 |
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|a Visual Dialog
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|c 2018
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|a Date Revised 27.02.2024
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|a published: Print-Electronic
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|a Citation Status Publisher
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|a We introduce the task of Visual Dialog, which requires an AI agent to hold a meaningful dialog with humans in natural, conversational language about visual content. Specifically, given an image, a dialog history, and a question about the image, the agent has to ground the question in image, infer context from history, and answer the question accurately. Visual Dialog is disentangled enough from a specific downstream task so as to serve as a general test of machine intelligence, while being sufficiently grounded in vision to allow objective evaluation of individual responses and benchmark progress. We develop a novel two-person real-time chat data-collection protocol to curate a large-scale Visual Dialog dataset (VisDial). VisDial v0.9 has been released and consists of dialog question-answer pairs from 10-round, human-human dialogs grounded in images from the COCO dataset
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|a Journal Article
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|a Kottur, Satwik
|e verfasserin
|4 aut
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|a Gupta, Khushi
|e verfasserin
|4 aut
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| 700 |
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|a Singh, Avi
|e verfasserin
|4 aut
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| 700 |
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|a Yadav, Deshraj
|e verfasserin
|4 aut
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| 700 |
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|a Lee, Stefan
|e verfasserin
|4 aut
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| 700 |
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|a Moura, Jose
|e verfasserin
|4 aut
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|a Parikh, Devi
|e verfasserin
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|a Batra, Dhruv
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g (2018) vom: 19. Apr.
|w (DE-627)NLM098212257
|x 1939-3539
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| 773 |
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|g year:2018
|g day:19
|g month:04
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|u http://dx.doi.org/10.1109/TPAMI.2018.2828437
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