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AGQA 2.0: An Updated Benchmark for Compositional Spatio-Temporal Reasoning (2204.06105v1)

Published 12 Apr 2022 in cs.CV

Abstract: Prior benchmarks have analyzed models' answers to questions about videos in order to measure visual compositional reasoning. Action Genome Question Answering (AGQA) is one such benchmark. AGQA provides a training/test split with balanced answer distributions to reduce the effect of linguistic biases. However, some biases remain in several AGQA categories. We introduce AGQA 2.0, a version of this benchmark with several improvements, most namely a stricter balancing procedure. We then report results on the updated benchmark for all experiments.

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Authors (3)
  1. Madeleine Grunde-McLaughlin (8 papers)
  2. Ranjay Krishna (116 papers)
  3. Maneesh Agrawala (42 papers)
Citations (13)

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