BEVTrack Benchmark

The BEVTrack benchmark consists of two complementary datasets: CVMHAT-BEVT and BEVT-S, designed for multi-view human tracking with bird's-eye view (BEV) capabilities. CVMHAT-BEVT is adapted from the public CVMHAT dataset, featuring 21 synchronous multi-view videos across five scenes, with 7-12 individuals per scene and video durations ranging from 200 to 1,500 frames. Each scene contains 2-4 side views and includes synchronized BEV footage captured by drones, along with annotated bounding boxes and unified ID numbers for all subjects across views.To address the limitations of real-world datasets, we introduce BEVT-S, a large-scale synthetic dataset created using Unity 3D engine and PersonX model library. BEVT-S comprises five diverse scenes, each spanning 25m × 25m and containing 15-20 individuals with varied walking trajectories. The dataset includes 75 pairs of first-person view (FPV) videos (50 for training, 25 for testing), with each scene running for 1,000 frames. BEVT-S provides comprehensive annotations including subject positions (in meters), body orientations in BEV, camera poses, and unified bounding box IDs across all views. This synthetic dataset enables robust training and evaluation of multi-view human tracking systems with BEV integration.