Research map / Detection and segmentation / Tracking
A Unified Object Motion and Affinity Model for Online Multi-Object Tracking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| unify SOT motion prediction and affinity metric learning in one triplet network | UMA · MOT16 test | MOTA | Mixed |
| unify SOT motion prediction and affinity metric learning in one triplet network | UMA · MOT16 test | speed | Helped |
| unify SOT motion prediction and affinity metric learning in one triplet network | UMA · MOT17 test | IDF1: 52.3 -> 54.4 | Mixed |
| add joint N-pair and identification losses to SOT training (ablation) | UMA without TSA · MOT17-09, MOT17-10 validation | IDF1: 48.1 -> 58.6 | Helped |
| add joint N-pair and identification losses to SOT training (ablation) | UMA without TSA · MOT17-09, MOT17-10 validation | MOTA: 50.4 -> 52.4 | Helped |
| add N-pair loss instead of triplet loss (ablation) | UMA without TSA or identification loss · MOT17-09, MOT17-10 validation | IDF1: 50.9 -> 53.1 | Helped |
| add identification loss alongside N-pair loss (ablation) | UMA without TSA · MOT17-09, MOT17-10 validation | IDF1: 53.1 -> 58.6 | Helped |
| add TSA task-specific attention (ablation) | UMA with N-pair and identification losses · MOT17-09, MOT17-10 validation | MOTA: 52.4 -> 53.0 | Helped |
| add TSA task-specific attention (ablation) | UMA with N-pair and identification losses · MOT17-09, MOT17-10 validation | IDF1: 58.6 -> 61.9 | Helped |
Closest papers by meaning
- Focusing on Tracks for Online Multi-Object Tracking (CVPR 2025 · similarity 0.88)
- Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking (AAAI 2024 · similarity 0.86)
- Multiple Object Tracking as ID Prediction (CVPR 2025 · similarity 0.85)
- Multi-Scene Generalized Trajectory Global Graph Solver with Composite Nodes for Multiple Object Tracking (AAAI 2024 · similarity 0.85)
- Towards Generalizable Multi-Object Tracking (CVPR 2024 · similarity 0.85)
- Sampling-Resilient Multi-Object Tracking (AAAI 2024 · similarity 0.85)
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