Transcription of SPICE: Semantic Propositional Image Caption …
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SPICE: Semantic Propositional Image Caption …
SPICE: Semantic Propositional Image CaptionEvaluationPeter Anderson1, Basura Fernando1, Mark Johnson2, Stephen Gould11 The Australian National University, Canberra, University, Sydney, is considerable interest in the task of automaticallygenerating Image captions. However, evaluation is challenging. Existingautomatic evaluation metrics are primarily sensitive to n-gram overlap,which is neither necessary nor sufficient for the task of simulating hu-man judgment. We hypothesize that Semantic Propositional content is animportant component of human Caption evaluation , and propose a newautomated Caption evaluation metric defined over scene graphs coinedSPICE. Extensive evaluations across a range of models and datasetsindicate that SPICE captures human judgments over model-generatedcaptions better than other automatic metrics ( , system-level corre-lation of with human judgments on the MS COCO dataset, for CIDEr and for METEOR).
SPICE: Semantic Propositional Image Caption Evaluation 3 important component of human caption evaluation. That is, given an image with the caption ‘A young girl standing on top of a tennis court’, we expect that a
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