Research map / Detection and segmentation / Tracking
MPM: Joint Representation of Motion and Position Map for Cell Tracking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Jointly encode cell-position likelihood and motion association in one MPM instead of estimating them independently | MPM cell tracking · Average across four culture conditions | association accuracy: 0.912 -> 0.969 (+5.7%) | Helped |
| Jointly encode cell-position likelihood and motion association in one MPM instead of estimating them independently | MPM cell tracking · Average across four culture conditions | target effectiveness: 0.822 -> 0.875 (+5.1%) | Helped |
| Use two successive frames as context for cell-position estimation | MPM cell detection · Fully annotated test sequences | recall: 0.902 -> 0.932 (+1.4%) | Helped |
| Add a magnitude-error term to the MPM training loss (ablation) | MPM-Net · MPM training | training stability | Helped |
Closest papers by meaning
- Higher-Order Cell Tracking Transformer (NeurIPS 2026 · similarity 0.85)
- TrackingWorld: World-centric Monocular 3D Tracking of Almost All Pixels (NeurIPS 2025 · similarity 0.84)
- Track-On: Transformer-based Online Point Tracking with Memory (ICLR 2025 · similarity 0.83)
- TrackCraft3R: Repurposing Video Diffusion Transformers for Dense 3D Tracking (NeurIPS 2026 · similarity 0.83)
- Video Diffusion Models Excel at Tracking Similar-Looking Objects Without Supervision (NeurIPS 2025 · similarity 0.83)
- DiffusionTrack: Diffusion Model for Multi-Object Tracking (AAAI 2024 · similarity 0.83)
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