Research map / Video / Action recognition
Dance With Flow: Two-In-One Stream Action Detection
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Condition RGB features on optical flow using motion modulation | RGB-stream SSD · UCF101-24 | mAP: 18.49 -> 20.15 | Helped |
| Replace the separate RGB and flow streams with one flow-conditioned stream | SSD action detector · UCF101-24 | mAP: 19.79 -> 20.15 | Helped |
| Add a separate flow stream and fuse it with Two-in-one | Two-in-one detector · UCF101-24 | mAP: 20.15 -> 22.02 | Helped |
| Add a separate flow stream and fuse it with Two-in-one | Two-in-one detector · J-HMDB | mAP@IoU 0.50:0.95: 38.72 -> 43.20 | Helped |
| Use a 3x3 kernel in the last motion-condition layer instead of 1x1 kernels throughout (ablation) | Two-in-one stream · UCF101-24 | mAP: about 1.5% | Helped |
| Place the modulation layer in deeper convolutional layers rather than bottom layers (ablation) | Two-in-one stream · UCF101-24 | mAP | Hurt |
| Apply modulation layers to multiple convolutional layers instead of a single layer (ablation) | Two-in-one stream · UCF101-24 | mAP | No clear effect |
| Use appearance features to modulate the flow stream instead of using flow to modulate RGB (ablation) | Two-in-one stream · Action detection | detection accuracy | Hurt |
| Use more accurate BroxFlow rather than FlowNet flow images (ablation) | Two-in-one stream · UCF101-24 | mAP: 19.97 -> 21.51 | Helped |
| Use noisy RealTimeFlow rather than BroxFlow (ablation) | Two-in-one stream · UCF101-24 | mAP: 21.51 -> 19.16 | Hurt |
| Use flow-conditioned RGB modulation rather than an RGB-only stream | Single-frame detector · J-HMDB | mAP@IoU 0.50:0.95: 41.60 -> 38.72 | Hurt |
Closest papers by meaning
- MARS: Motion-Augmented RGB Stream for Action Recognition (CVPR 2019 · similarity 0.90)
- Im2Flow: Motion Hallucination From Static Images for Action Recognition (CVPR 2018 · similarity 0.88)
- Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition (CVPR 2018 · similarity 0.87)
- A Multi-Stream Bi-Directional Recurrent Neural Network for Fine-Grained Action Detection (CVPR 2016 · similarity 0.87)
- StreamFlow: Streamlined Multi-Frame Optical Flow Estimation for Video Sequences (NeurIPS 2024 · similarity 0.85)
- FlowFeat: Pixel-Dense Embedding of Motion Profiles (NeurIPS 2025 · similarity 0.84)
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