Papers › Lifting Multi-View Detection and Tracking to the Bird's Eye View
Lifting Multi-View Detection and Tracking to the Bird's Eye View
Torben Teepe, Philipp Wolters, Johannes Gilg, Fabian Herzog, Gerhard Rigoll
Taking advantage of multi-view aggregation presents a promising solution to tackle challenges such as occlusion and missed detection in multi-object tracking and detection. Recent advancements in multi-view detection and 3D object recognition have significantly improved performance by strategically projecting all views onto the ground plane and conducting detection analysis from a Bird's Eye View. In this paper, we compare modern lifting methods, both parameter-free and parameterized, to multi-view aggregation. Additionally, we present an architecture that aggregates the features of multiple times steps to learn robust detection and combines appearance- and motion-based cues for tracking. Most current tracking approaches either focus on pedestrians or vehicles. In our work, we combine both branches and add new challenges to multi-view detection with cross-scene setups. Our method generalizes to three public datasets across two domains: (1) pedestrian: Wildtrack and MultiviewX, and (2) roadside perception: Synthehicle, achieving state-of-the-art performance in detection and tracking. https://github.com/tteepe/TrackTacular
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Code
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Tasks
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multi-Object Tracking | MultiviewX | TrackTacular (Bilinear Sampling) | IDF1 | 85.6 | #1 of 2 | Archive leaderboard | report |
| Multi-Object Tracking | MultiviewX | TrackTacular (Bilinear Sampling) | MOTA | 92.4 | #1 of 2 | Archive leaderboard | report |
| Multi-Object Tracking | Wildtrack | TrackTacular (Bilinear Sampling) | IDF1 | 95.3 | #2 of 9 | Archive leaderboard | report |
| Multi-Object Tracking | Wildtrack | TrackTacular (Bilinear Sampling) | MOTA | 91.8 | #2 of 9 | Archive leaderboard | report |
| Multiview Detection | MultiviewX | TrackTacular (Bilinear Sampling) | MODA | 96.5 | #2 of 9 | Archive leaderboard | report |
| Multiview Detection | MultiviewX | TrackTacular (Bilinear Sampling) | MODP | 75.0 | #2 of 9 | Archive leaderboard | report |
| Multiview Detection | MultiviewX | TrackTacular (Bilinear Sampling) | Recall | 97.1 | #2 of 9 | Archive leaderboard | report |
| Multiview Detection | Wildtrack | TrackTacular (Depth Splatting) | MODA | 93.2 | #3 of 10 | Archive leaderboard | report |
| Multiview Detection | Wildtrack | TrackTacular (Depth Splatting) | MODP | 77.5 | #3 of 10 | Archive leaderboard | report |
| Multiview Detection | Wildtrack | TrackTacular (Depth Splatting) | Recall | 95.8 | #3 of 10 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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