Papers › Dance with Flow: Two-in-One Stream Action Detection
Dance with Flow: Two-in-One Stream Action Detection
Jiaojiao Zhao, Cees G. M. Snoek
The goal of this paper is to detect the spatio-temporal extent of an action. The two-stream detection network based on RGB and flow provides state-of-the-art accuracy at the expense of a large model-size and heavy computation. We propose to embed RGB and optical-flow into a single two-in-one stream network with new layers. A motion condition layer extracts motion information from flow images, which is leveraged by the motion modulation layer to generate transformation parameters for modulating the low-level RGB features. The method is easily embedded in existing appearance- or two-stream action detection networks, and trained end-to-end. Experiments demonstrate that leveraging the motion condition to modulate RGB features improves detection accuracy. With only half the computation and parameters of the state-of-the-art two-stream methods, our two-in-one stream still achieves impressive results on UCF101-24, UCFSports and J-HMDB.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Action Detection | J-HMDB | Two-in-one Two Stream | Video-mAP 0.5 | 74.74 | #16 of 18 | Archive leaderboard | report |
| Action Detection | J-HMDB | Two-in-one | Video-mAP 0.5 | 57.96 | #17 of 18 | Archive leaderboard | report |
| Action Detection | UCF Sports | Two-in-one Two Stream | Video-mAP 0.5 | 96.52 | #6 of 7 | Archive leaderboard | report |
| Action Detection | UCF Sports | Two-in-one | Video-mAP 0.5 | 92.74 | #7 of 7 | Archive leaderboard | report |
| Action Detection | UCF101-24 | Two-in-one Two Stream | Video-mAP 0.2 | 78.48 | #17 of 19 | Archive leaderboard | report |
| Action Detection | UCF101-24 | Two-in-one Two Stream | Video-mAP 0.5 | 50.30 | #17 of 19 | Archive leaderboard | report |
| Action Detection | UCF101-24 | Two-in-one | Video-mAP 0.2 | 75.48 | #18 of 19 | Archive leaderboard | report |
| Action Detection | UCF101-24 | Two-in-one | Video-mAP 0.5 | 48.31 | #18 of 19 | Archive leaderboard | report |
| Action Recognition | UCF101 | two-in-one two stream | 3-fold Accuracy | 92 | #65 of 91 | 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.
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