ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions

no code implementations • 23 Apr 2024 • Shounak Sural, Nishad Sahu, Ragunathan, Rajkumar

The fusion of multimodal sensor data streams such as camera images and lidar point clouds plays an important role in the operation of autonomous vehicles (AVs).

CurbScan: Curb Detection and Tracking Using Multi-Sensor Fusion

no code implementations • 9 Oct 2020 • Iljoo Baek, Tzu-Chieh Tai, Manoj Bhat, Karun Ellango, Tarang Shah, Kamal Fuseini, Ragunathan, Rajkumar

In this paper, we propose an approach to detect and track curbs by fusing together data from multiple sensors: sparse LiDAR data, a mono camera and low-cost ultrasonic sensors.

Autonomous Driving Sensor Fusion

Point-GNN: Graph Neural Network for 3D Object Detection in a Point Cloud

1 code implementation • CVPR 2020 • Weijing Shi, Ragunathan, Rajkumar

In this paper, we propose a graph neural network to detect objects from a LiDAR point cloud.

3D Object Detection object-detection +1

Real-time Detection, Tracking, and Classification of Moving and Stationary Objects using Multiple Fisheye Images

no code implementations • 16 Mar 2018 • Iljoo Baek, Albert Davies, Geng Yan, Ragunathan, Rajkumar

The ability to detect pedestrians and other moving objects is crucial for an autonomous vehicle.

General Classification Moving Object Detection +1