Today's status quo is to either uniformly collect N answers for every visual question <cite>[3]</cite> or collect multiple answers where the number is determined by external crowdsourcing conditions [1] . Our system instead spends a human budget by predicting the number of answers to collect Fig. 6 : We propose a novel application of predicting the number of redundant answers to collect from the crowd per visual question to efficiently capture the diversity of all answers for all visual questions.