Semantic-Aware Pretraining for Dense Video Captioning
Southern University of Science and Technology（南方科技大学）；The University of Hong Kong（香港大学）
英文摘要：
This report describes the details of our approach for the event dense-captioning task in ActivityNet Challenge 2021. We present a semantic-aware pretraining method for dense video captioning, which empowers the learned features to recognize high-level semantic concepts. Diverse video features of different modalities are fed into an event captioning module to generate accurate and meaningful sentences. Our final ensemble model achieves a 10.00 METEOR score on the test set.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
