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Prior benchmarks have analyzed models' answers to questions about videos in order to measure visual compositional reasoning.
Heterogeneous memory enhanced multimodal attention model for video question answering
Chenyou Fan, Xiaofan Zhang, Shu Zhang, Wensheng Wang, Chi Zhang, and Heng Huang · 2019
Earlier work this paper cites.
Beyond rnns: Positional self-attention with co-attention for video question answering
Xiangpeng Li, Jingkuan Song, Lianli Gao, Xianglong Liu, Wenbing Huang, Xiangnan He, and Chuang Gan · 2019
Earlier work this paper cites.
Repair: Removing representation bias by dataset resampling
Yi Li and Nuno Vasconcelos · 2019
Cited alongside, same era.
Hierarchical conditional relation networks for video question answering
Thao Minh Le, Vuong Le, Svetha Venkatesh, and Truyen Tran · 2020
Cited alongside, same era.
What gives the answer away? question answering bias analysis on video qa datasets
Jianing Yang, Yuying Zhu, Yongxin Wang, Ruitao Yi, Amir Zadeh, and Louis-Philippe Morency · 2020
Later among the works it cites.
Agqa: A benchmark for compositional spatio-temporal reasoning
Madeleine Grunde-McLaughlin, Ranjay Krishna, and Maneesh Agrawala · 2021
Later among the works it cites.
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