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Found 5 papers, 4 papers with code
Leveraging Anchor-based LiDAR 3D Object Detection via Point Assisted Sample Selection
3D object detection based on LiDAR point cloud and prior anchor boxes is a critical technology for autonomous driving environment perception and understanding.
Influence of Spattering on In-process Layer Surface Roughness during Laser Powder Bed Fusion
In this work, using our lab-designed LPBF-specific fringe projection profilometry and an off-axis camera, we quantify the correlation between MP spattering and in-process layer surface roughness for the first time to reveal the influence of MP spatters on process anomaly and part defects.
3D Harmonic Loss: Towards Task-consistent and Time-friendly 3D Object Detection on Edge for V2X Orchestration
Edge computing-based 3D perception has received attention in intelligent transportation systems (ITS) because real-time monitoring of traffic candidates potentially strengthens Vehicle-to-Everything (V2X) orchestration.
Predicting Pedestrian Crossing Intention with Feature Fusion and Spatio-Temporal Attention
This work addresses the above limitations by introducing a novel neural network architecture to fuse inherently different spatio-temporal features for pedestrian crossing intention prediction.
Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using Fusion
The main strategy is to depend solely on the 2D vision for recognizing object class, as object shape does not change drastically with an increase in depth, and use pointcloud data for object localization in the 3D space for faraway objects.
