nuScenes: A multimodal dataset for autonomous driving

Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle technology. Image based benchmark datasets have driven development in computer vision tasks such as object detection, tracking and segmentation of agents in the environment... (read more)

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Datasets


Introduced in the Paper:

nuScenes

Mentioned in the Paper:

ImageNet KITTI Cityscapes ApolloScape H3D A*3D

Results from the Paper


Ranked #36 on 3D Object Detection on nuScenes (using extra training data)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
RESULT BENCHMARK
3D Object Detection nuScenes PointPillars NDS 0.442 # 39
3D Object Detection nuScenes PointPillars (KITTI) NDS 0.448 # 38
3D Object Detection nuScenes PointPillars (ImageNet) NDS 0.449 # 36

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet