BRITE benchmark reveals that leading T2V models handle static object composition well but degrade sharply on object-action binding and audio-visual synchronization for implausible prompts.
Proceedings of the 42nd International Conference on Machine Learning (ICML) , series =
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BRITE: A Benchmark for Reliable and Interpretable T2V Evaluation on Implausible Scenarios
BRITE benchmark reveals that leading T2V models handle static object composition well but degrade sharply on object-action binding and audio-visual synchronization for implausible prompts.