Discriminability objective for training descriptive captions
نویسندگان
چکیده
•ATTN models better than FC models, and discriminability objective works for both. •ATTN+CIDEr+* combination is our best choice •Moderate λ = 1 produces good tradeoff between discriminability and fluency •Higher λ make captions more discriminative to machine and to humans, but at the cost of fluency •With moderate λ, non-discriminative scores like BLEU, METEOR, CIDEr improve as well! • especially surprising result: CIDEr (ostensibly we focus less on maximizing it during training.)
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