iCap: Interactive Image Captioning with Predictive Text

January 31, 2020 Β· Declared Dead Β· πŸ› International Conference on Multimedia Retrieval

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Authors Zhengxiong Jia, Xirong Li arXiv ID 2001.11782 Category cs.HC: Human-Computer Interaction Cross-listed cs.CV Citations 9 Venue International Conference on Multimedia Retrieval Last Checked 4 months ago
Abstract
In this paper we study a brand new topic of interactive image captioning with human in the loop. Different from automated image captioning where a given test image is the sole input in the inference stage, we have access to both the test image and a sequence of (incomplete) user-input sentences in the interactive scenario. We formulate the problem as Visually Conditioned Sentence Completion (VCSC). For VCSC, we propose asynchronous bidirectional decoding for image caption completion (ABD-Cap). With ABD-Cap as the core module, we build iCap, a web-based interactive image captioning system capable of predicting new text with respect to live input from a user. A number of experiments covering both automated evaluations and real user studies show the viability of our proposals.
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