An increasing amount of work on the Visual Question Answering (VQA) task (Antol et al., 2015;Lu et al., 2016) has also looked into more interpretable approaches, for example, by utilizing attention-based models (Fukui et al., 2016) or reasoning based on explicit evidence (Wang et al., 2017).
for action understanding, recent work explicitly models commonsense knowledge including causal relations (Gao et al., 2016;Forbes and Choi, 2017;Zellers and Choi, 2017;Gao et al., 2018) related to concrete actions, which can facilitate action explanation.