Research map / Detection and segmentation / Tracking
A Twofold Siamese Network for Real-Time Object Tracking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| combine semantic and appearance branches (ablation) | SiamFC · OTB-2013 | AUC: 0.599 / 0.607 -> 0.649 | Helped |
| add multilevel semantic features (ablation) | SA-Siam · OTB-2013 | AUC: 0.649 -> 0.656 | Helped |
| add multilevel semantic features (ablation) | SA-Siam · OTB-50 | AUC: 0.583 -> 0.581 | Hurt |
| add channel attention (ablation) | SA-Siam · OTB-50 | AUC: 0.583 -> 0.591 | Helped |
| add channel attention (ablation) | SA-Siam · OTB-100 | AUC: 0.637 -> 0.642 | Helped |
| use heterogeneous semantic and appearance models rather than ensembles of similar models (ablation) | SA-Siam · OTB-2013 | AUC: A1A2: 0.608; S1S2: 0.602; SA-Siam: 0.649 | Helped |
| jointly train the two branches instead of training separately (ablation) | SA-Siam · OTB-2013/50/100 | AUC: 0.630, 0.546, 0.620 | Hurt |
| use three-scale search | SA-Siam · object tracking | speed | Mixed |
| fine-tune S-Net | SA-Siam · object tracking | tracking performance | Hurt |
Closest papers by meaning
- Deformable Siamese Attention Networks for Visual Object Tracking (CVPR 2020 · similarity 0.91)
- Graph Attention Tracking (CVPR 2021 · similarity 0.90)
- Deeper and Wider Siamese Networks for Real-Time Visual Tracking (CVPR 2019 · similarity 0.90)
- High Performance Visual Tracking With Siamese Region Proposal Network (CVPR 2018 · similarity 0.90)
- Siam R-CNN: Visual Tracking by Re-Detection (CVPR 2020 · similarity 0.90)
- Correlation-Aware Deep Tracking (CVPR 2022 · similarity 0.88)
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