Introduction Short-form video content has exploded on social platforms. Users prefer concise summaries highlighting salient moments. Existing summarization approaches often target longer videos and focus on visual features alone. This work proposes a lightweight multi-modal model optimized for clips around one minute in length, combining frame-level visual embeddings, audio features, and automatic speech recognition (ASR) transcripts via a cross-modal attention mechanism.
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