The IITB Predicting Media Interestingness System for MediaEval 2017
نویسندگان
چکیده
This paper describes the system developed by team IITB for MediaEval 2017 Predicting Media Interestingness Task. We propose a new method of training based on pairwise comparisons between frames of a trailer. The algorithm gave very promising results on the development set but did not impress on test set. Our highest achieved MAP@10 on test set is 0.0911 (Image subtask) and 0.0525 (Video subtask), based on a systems submitted last year ([4, 6]).
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