Transcript to Video: Efficient Clip Sequencing from Texts

Understand

Among numerous videos shared on the web, well-edited ones always attract more attention.

• However, it is difficult for inexperienced users to make well-edited videos because it requires professional expertise and immense manual labor.
• To meet the demands for non-experts, we present Transcript-to-Video -- a weakly-supervised framework that uses texts as input to automatically create video sequences from an extensive collection of shots.
• Specifically, we propose a Content Retrieval Module and a Temporal Coherent Module to learn visual-language representations and model shot sequencing styles, respectively.