Research map / Detection and segmentation / Tracking
Multiple Object Tracking With Correlation Learning
Check your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add spatial local correlation to FairMOT (ablation) | FairMOT · MOT17 validation | IDF1: 72.9% -> 75.8% | Helped |
| Replace local correlation with a non-local module (ablation) | FairMOT · MOT17 validation | MOTA: 69.1% -> 67.7% | Hurt |
| Add temporal local correlation (ablation) | FairMOT with spatial correlation · MOT17 validation | MOTA: 69.1% -> 70.9% | Helped |
| Add both spatial and temporal local correlation (ablation) | FairMOT · MOT17 validation | IDF1: 72.9% -> 76.1% | Helped |
| Add long-term memory to STLC (ablation) | STLC · MOT17 validation | MOTA: 71.5% -> 72.1% | Helped |
| Add tracking supervision loss (ablation) | STLC+LT · MOT17 validation | IDF1: 75.6% -> 76.1% | Helped |
| Add self-supervised loss (ablation) | STLC+LT · MOT17 validation | IDF1: 75.6% -> 77.6% | Helped |
| Increase local correlation region size (ablation) | CorrTracker · MOT17 validation | MOTA | Mixed |
| Use feature concatenation for temporal cues instead of temporal local correlation (ablation) | FairMOT · MOT17 validation | MOTA: +0.2% and +1.3% | Helped |
| Add local correlation tracking to FairMOT | FairMOT · MOT17 test | MOTA: 73.7 -> 76.5 | Helped |
| Add local correlation tracking to FairMOT | FairMOT · MOT20 test | MOTA: 61.8 -> 65.2 | Helped |
Closest papers by meaning
- Video Modeling With Correlation Networks (CVPR 2020 · similarity 0.89)
- Correlation-Aware Deep Tracking (CVPR 2022 · similarity 0.89)
- From Detection to Association: Learning Discriminative Object Embeddings for Multi-Object Tracking (CVPR 2026 · similarity 0.89)
- Unified Transformer Tracker for Object Tracking (CVPR 2022 · similarity 0.87)
- Multiple Object Tracking as ID Prediction (CVPR 2025 · similarity 0.87)
- Focusing on Tracks for Online Multi-Object Tracking (CVPR 2025 · similarity 0.86)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.