MoTIF adds temporal self-attention and automatic VLM-based concept discovery to concept bottleneck models for interpretable video classification, showing gains over prior global CBMs on benchmarks.
Revisiting multiple instance neural networks
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Concepts in Motion: Temporal Concept Bottleneck Model for Interpretable Video Classification
MoTIF adds temporal self-attention and automatic VLM-based concept discovery to concept bottleneck models for interpretable video classification, showing gains over prior global CBMs on benchmarks.