Vehicle Pose Estimation On Kitti Cars Hard
평가 지표
Average Orientation Similarity
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Average Orientation Similarity |
|---|---|
| 3d-bounding-box-estimation-using-deep | 76.76 |
| monocular-3d-object-detection-leveraging | 72.26 |
| rtm3d-real-time-monocular-3d-detection-from | 77.18 |
| 3d-rcnn-instance-level-3d-object | 80.07 |
| m3d-rpn-monocular-3d-region-proposal-network | 67.08 |
| exploring-intermediate-representation-for | 80.96 |
| monopair-monocular-3d-object-detection-using | 76.45 |
| learning-depth-guided-convolutions-for | 63.98 |
| multi-level-fusion-based-3d-object-detection | 76.37 |
| disp-r-cnn-stereo-3d-object-detection-via | 67.16 |
| dsgn-deep-stereo-geometry-network-for-3d | 78.27 |
| reinforced-axial-refinement-network-for | 66.90 |
| monocular-3d-object-detection-for-autonomous | 76.84 |
| subcategory-aware-convolutional-neural | 78.68 |
| deep-fitting-degree-scoring-network-for | 76.85 |
| deep-manta-a-coarse-to-fine-many-task-network | 80.39 |
| gs3d-an-efficient-3d-object-detection | 61.85 |
| 3d-object-proposals-for-accurate-object-class | 76.52 |
| kinematic-3d-object-detection-in-monocular | 34.81 |