Feature-modulating methods like FiLM (De Vries et al., 2017;Perez et al., 2018) control image-comprehension process using modulation-parameters generated from the question, allowing models to be trained end-to-end.
questions in CLEVR cover several typical elements of reasoning: counting, comparing, querying the memory, etc.