Research map / Detection and segmentation / Tracking
Detect or Track: Towards Cost-Effective Video Object Detection/Tracking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a learned scheduler to choose between detection and tracking instead of fixed frame skipping | DorT · ImageNet VID video object detection/tracking | mAP | Helped |
| Use RoI convolution instead of crop-and-resize SiamFC for multi-box tracking (ablation) | DorT · ImageNet VID | speed: over 10x; 3 fps -> 54 fps | Helped |
| Use RoI convolution instead of crop-and-resize SiamFC for multi-box tracking (ablation) | DorT · ImageNet VID | mAP: 56.5\% | No clear effect |
| Use DorT rather than deep feature flow with Hungarian association | Video object detection/tracking · ImageNet VID | mAP | Helped |
| Use DorT rather than deep feature flow | Video object detection · ImageNet VID | speed | Helped |
| Use DorT rather than deep feature flow | Video object detection · ImageNet VID | mAP: no more than 1% mAP loss | No clear effect |
| Set the scheduler track-decision threshold to 0.97 for conservative tracking decisions | DorT scheduler · ImageNet VID | false positive rate: 1.9% | Helped |
Closest papers by meaning
- A Distractor-Aware Memory for Visual Object Tracking with SAM2 (CVPR 2025 · similarity 0.85)
- Focusing on Tracks for Online Multi-Object Tracking (CVPR 2025 · similarity 0.85)
- VastTrack: Vast Category Visual Object Tracking (NeurIPS 2024 · similarity 0.84)
- TrackIME: Enhanced Video Point Tracking via Instance Motion Estimation (NeurIPS 2024 · similarity 0.84)
- DiffusionTrack: Diffusion Model for Multi-Object Tracking (AAAI 2024 · similarity 0.83)
- SMILEtrack: SiMIlarity LEarning for Occlusion-Aware Multiple Object Tracking (AAAI 2024 · similarity 0.83)
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