Temporal Localization of Moments in Video Collections with Natural Language
Table 6: Text to video retrieval results. We show Recall@K on MSR-VTT [36], DiDeMo [16], and Charades-STA [10] with RGB features. See text for more details.
['Dataset', 'Method', 'R@1', 'R@10', 'R@100', 'MR ↓']
We used the publicly available implementation of MEE to retrieve videos from the corpus and turned off flow, face and audio features in MEE for fair comparison. For our two-stage retrieval baseline of moments from a video corpus for a natural language query, we tested MEE models pre-trained on MSR-VTT and the corresponding dataset. We observed that MEE pre-trained on MSR-VTT performed near chance; while re-training MEE on the target datasets performed the best. Thus, we used the latter setup in the rest of the experiments in our main submission.