2018 Winners
Track 1: Traffic Flow Analysis
1st Place: Team 48 from University of Washington
2nd Place: Team 79 from Beihang University, Shanghai Jiao Tong University, University of Chinese Academy of Sciences, and University of Southern California
| Team | S1 | DR | RMSE | #S |
| 48 | 1 | 100.00% | 4.096 | 41 |
| 79 | 0.9162 | 100.00% | 6.041 | 24 |
| 78 | 0.8892 | 100.00% | 6.667 | 22 |
| 24 | 0.8813 | 100.00% | 6.849 | 10 |
| 12 | 0.8331 | 100.00% | 7.97 | 13 |
| 4 | 0.7924 | 100.00% | 8.914 | 13 |
| 65 | 0.7654 | 100.00% | 9.541 | 8 |
| 6 | 0.7174 | 81.48% | 6.869 | 22 |
| 40 | 0.6564 | 81.48% | 8.609 | 5 |
| 26 | 0.6547 | 100.00% | 12.109 | 7 |
| 18 | 0.6264 | 85.19% | 10.34 | 11 |
| 45 | 0.5953 | 96.29% | 12.957 | 10 |
| 39 | 0 | 88.89% | 27.302 | 4 |
Track 2: Anomaly Detection
1st Place: Team 15 from Panasonic R&D Center Singapore, Huazhong University of Science and Technology, Nanyang Technological University, and Chinese Academy of Sciences
2nd Place: Team 63 from Beijing University of Posts and Telecommunications
| Team | S2 | F1 | RMSE | #S |
| 15 | 0.8649 | 0.8649 | 3.6152 | 24 |
| 63 | 0.7853 | 0.8108 | 10.2369 | 19 |
| 18 | 0.4951 | 0.6286 | 48.3406 | 9 |
| 25 | 0.2638 | 0.4762 | 97.5505 | 11 |
| 39 | 0.064 | 0.2363 | 157.2298 | 12 |
| 79 | 0.0069 | 0.7567 | 212.3274 | 3 |
| 12 | 0 | 0.7692 | 214.2712 | 4 |
Track 3: Multi-sensor Vehicle Detection and Reidentification
1st Place: Team 48 from University of Washington
2nd Place: Team 37 from National Taiwan University
| Team | S3 | TDR | PR | #S |
| 48 | 0.7106 | 0.4286 | 0.9925 | 22 |
| 37 | 0.2861 | 0.5714 | 0.0007 | 20 |
| 79 | 0.0785 | 0.1429 | 0.0142 | 17 |
| 18 | 0.0074 | 0 | 0.0147 | 22 |
| 28 | 0.0026 | 0 | 0.0052 | 6 |
| 41 | 0.0024 | 0 | 0.0049 | 6 |
| 53 | 0.0002 | 0 | 0.0004 | 1 |
| 6 | 0.0001 | 0 | 0.0001 | 11 |
| 10 | 0 | 0 | 0 | 1 |
| 31 | 0 | 0 | 0 | 1 |