Search Results for author:
Found 7 papers, 3 papers with code
VirtualPainting: Addressing Sparsity with Virtual Points and Distance-Aware Data Augmentation for 3D Object Detection
In recent times, there has been a notable surge in multimodal approaches that decorates raw LiDAR point clouds with camera-derived features to improve object detection performance.
SiCP: Simultaneous Individual and Cooperative Perception for 3D Object Detection in Connected and Automated Vehicles
Cooperative perception for connected and automated vehicles is traditionally achieved through the fusion of feature maps from two or more vehicles.
Online Self-Evolving Anomaly Detection in Cloud Computing Environments
As a distinct advantage of our framework, cloud system administrators only need to check a small number of detected anomalies, and their decisions are leveraged to update the detector.
Receptivity and stability of hypersonic leading-edge sweep flows around a blunt body
We establish an adjoint-based bi-orthogonal eigenfunction system to address the receptivity problem of such flows to any external forces and boundary perturbations.
Fluid Dynamics
CoFF: Cooperative Spatial Feature Fusion for 3D Object Detection on Autonomous Vehicles
To reduce the amount of transmitted data, feature map based fusion is recently proposed as a practical solution to cooperative 3D object detection by autonomous vehicles.
DCANet: Learning Connected Attentions for Convolutional Neural Networks
With DCANet, all attention blocks in a CNN model are trained jointly, which improves the ability of attention learning.
Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds
A point cloud based 3D object detection method is proposed to work on a diversity of aligned point clouds.
Ranked #3 on
3D Object Detection
on OPV2V
