BDD100K
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Semantic Segmentation | BDD100K (val) | mIoU67.59 | 72 | |
| Multi-Object Tracking | BDD100K (val) | mIDF158.8 | 70 | |
| Semantic Segmentation | BDD100K night | mIoU50.42 | 65 | |
| Object Detection | BDD100K (val) | mAP47.8 | 60 | |
| Semantic Segmentation | BDD100K (test) | mIoU64.6 | 58 | |
| Multi-Object Tracking and Segmentation | BDD100K segmentation tracking (val) | mMOTSA35.7 | 54 | |
| Object Detection | BDD100K (test) | mAP@0.5053.4 | 48 | |
| Multi-Object Tracking | BDD100K (test) | Mean IDF160 | 36 | |
| Lane Segmentation | BDD100K v1.0 (test) | IoU34.2 | 36 | |
| Lane Detection | BDD100K (test) | Accuracy87.31 | 33 | |
| Object Detection | BDD100K (Nighttime) | AP49.5 | 26 | |
| Estimating data collection requirements | BDD100K Semi-supervised | Failure Rate2 | 24 | |
| Drivable Area Segmentation | BDD100K (test) | mIoU93.2 | 22 | |
| Object Detection | BDD100K | mAP51.3 | 19 | |
| Object Detection | Cityscapes → BDD100k | Truck AP66.9 | 18 | |
| Object Detection | BDD100K Cs→B adaptation (test) | mAP43.4 | 18 | |
| Object Detection | BDD100K series (test) | Session 1 Score52.1 | 16 | |
| Lane Segmentation | BDD100K (test) | mIoU34.2 | 16 | |
| Semantic Segmentation | BDD100K 19 class (val) | mIoU61.38 | 13 | |
| Traffic Object Detection | BDD100K | Recall89.4 | 13 | |
| Directly & Alternative Area Segmentation | BDD100K (test) | mIoU84.73 | 13 | |
| Object Detection | BDD100K time-of-day | Performance (Daytime)46.6 | 12 | |
| Object Detection | BDD100K weather | mAP (Rainy)0.373 | 12 | |
| Multi-task Perception | BDD100K | FPS802.9 | 12 | |
| Lane Detection | BDD100k | Accuracy88.6 | 12 |
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