2D Vehicle Detection on KITTI (test)
96.4AP (Easy)Deep MANTA
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Deep MANTASensor Type=Mono, Backbone=VGG162017.03 | 96.4 | 90.1 | 80.79 | |
| Deep MANTASensor Type=Mono, Backbone=GoogLeNet2017.03 | 95.77 | 90.03 | 80.62 | |
| 3DOPSensor Type=Stereo2017.03 | 93.04 | 88.64 | 79.1 | |
| Mono3DSensor Type=Mono2017.03 | 92.33 | 88.66 | 78.96 | |
| SubCNNSensor Type=Mono2017.03 | 90.81 | 89.04 | 79.27 | |
| F-PointNetClass=Car2018.12 | 90.78 | 90 | 80.8 | |
| IPODClass=Car2018.12 | 90.2 | 89.3 | 87.37 | |
| SDP + RPN2017.03 | 90.14 | 88.85 | 78.38 | |
| MS-CNN2017.03 | 90.03 | 89.02 | 76.11 | |
| AVOD-FPNClass=Car2018.12 | 89.99 | 87.44 | 80.05 | |
| AVODClass=Car2018.12 | 89.73 | 88.08 | 80.14 | |
| F-PointNetClass=Pedestrian2018.12 | 87.81 | 77.25 | 74.46 | |
| 3DVPSensor Type=Mono2017.03 | 87.46 | 75.77 | 65.38 | |
| Faster R-CNNSensor Type=Mono2017.03 | 86.71 | 81.84 | 71.12 | |
| F-PointNetClass=Cyclist2018.12 | 84.9 | 72.25 | 65.14 | |
| AOG2017.03 | 84.8 | 75.94 | 60.7 | |
| Regionlets2017.03 | 84.75 | 76.45 | 59.7 | |
| SubCat2017.03 | 84.14 | 75.46 | 59.71 | |
| IPODClass=Cyclist2018.12 | 82.9 | 65.28 | 57.63 | |
| OC-DPM2017.03 | 75.94 | 65.95 | 53.56 | |
| DPM-VOC+VP2017.03 | 74.95 | 64.71 | 48.76 | |
| IPODClass=Pedestrian2018.12 | 73.28 | 63.07 | 56.71 | |
| MDPM-un-BB2017.03 | 71.19 | 62.16 | 48.43 | |
| ACF-SC2017.03 | 69.11 | 58.66 | 45.95 | |
| AVOD-FPNClass=Cyclist2018.12 | 68.65 | 59.32 | 55.82 | |
| LSVM-MDPM-sv2017.03 | 68.2 | 56.48 | 44.18 | |
| AVOD-FPNClass=Pedestrian2018.12 | 67.32 | 58.42 | 57.44 | |
| AVODClass=Cyclist2018.12 | 65.72 | 56.01 | 48.89 | |
| AVODClass=Pedestrian2018.12 | 51.64 | 43.49 | 37.79 |