Research map / Detection and segmentation / Tracking
LaSOT: A High-Quality Benchmark for Large-Scale Single Object Tracking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Train SiamFC-3s (color) on LaSOT training data instead of ImageNet Video | SiamFC-3s (color) · OTB-2013 | precision: 0.803 -> 0.816 (↑1.3%) | Helped |
| Train SiamFC-3s (color) on LaSOT training data instead of ImageNet Video | SiamFC-3s (color) · OTB-2013 | success: 0.588 -> 0.608 (↑2.0%) | Helped |
| Train SiamFC-3s (color) on LaSOT training data instead of ImageNet Video | SiamFC-3s (color) · OTB-2015 | precision: 0.756 -> 0.777 (↑2.1%) | Helped |
| Train SiamFC-3s (color) on LaSOT training data instead of ImageNet Video | SiamFC-3s (color) · OTB-2015 | success: 0.565 -> 0.582 (↑1.7%) | Helped |
Closest papers by meaning
- VastTrack: Vast Category Visual Object Tracking (NeurIPS 2024 · similarity 0.89)
- SUTrack: Towards Simple and Unified Single Object Tracking (AAAI 2025 · similarity 0.88)
- OVT-B: A New Large-Scale Benchmark for Open-Vocabulary Multi-Object Tracking (NeurIPS 2024 · similarity 0.87)
- Track-On: Transformer-based Online Point Tracking with Memory (ICLR 2025 · similarity 0.86)
- M3SOT: Multi-Frame, Multi-Field, Multi-Space 3D Single Object Tracking (AAAI 2024 · similarity 0.86)
- DriveTrack: A Benchmark for Long-Range Point Tracking in Real-World Videos (CVPR 2024 · similarity 0.86)
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