Papers › A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer
A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer
Vladimir Iashin, Esa Rahtu
Dense video captioning aims to localize and describe important events in untrimmed videos. Existing methods mainly tackle this task by exploiting only visual features, while completely neglecting the audio track. Only a few prior works have utilized both modalities, yet they show poor results or demonstrate the importance on a dataset with a specific domain. In this paper, we introduce Bi-modal Transformer which generalizes the Transformer architecture for a bi-modal input. We show the effectiveness of the proposed model with audio and visual modalities on the dense video captioning task, yet the module is capable of digesting any two modalities in a sequence-to-sequence task. We also show that the pre-trained bi-modal encoder as a part of the bi-modal transformer can be used as a feature extractor for a simple proposal generation module. The performance is demonstrated on a challenging ActivityNet Captions dataset where our model achieves outstanding performance. The code is available: v-iashin.github.io/bmt
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Dense Video Captioning | ActivityNet Captions | BMT | BLEU-3 | 3.84 | #9 of 12 | Archive leaderboard | report |
| Dense Video Captioning | ActivityNet Captions | BMT | BLEU-4 | 1.88 | #9 of 12 | Archive leaderboard | report |
| Dense Video Captioning | ActivityNet Captions | BMT | METEOR | 8.44 | #9 of 12 | Archive leaderboard | report |
| Temporal Action Proposal Generation | ActivityNet Captions | BMT | Average F1 | 60.27 | #1 of 1 | Archive leaderboard | report |
| Temporal Action Proposal Generation | ActivityNet Captions | BMT | Average Precision | 48.23 | #1 of 1 | Archive leaderboard | report |
| Temporal Action Proposal Generation | ActivityNet Captions | BMT | Average Recall | 80.31 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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