3D-FFS: Faster 3D object detection with Focused Frustum Search in sensor fusion based networks

by   Aniruddha Ganguly, et al.

In this work we propose 3D-FFS, a novel approach to make sensor fusion based 3D object detection networks significantly faster using a class of computationally inexpensive heuristics. Existing sensor fusion based networks generate 3D region proposals by leveraging inferences from 2D object detectors. However, as images have no depth information, these networks rely on extracting semantic features of points from the entire scene to locate the object. By leveraging aggregated intrinsic properties (e.g. point density) of the 3D point cloud data, 3D-FFS can substantially constrain the 3D search space and thereby significantly reduce training time, inference time and memory consumption without sacrificing accuracy. To demonstrate the efficacy of 3D-FFS, we have integrated it with Frustum ConvNet (F-ConvNet), a prominent sensor fusion based 3D object detection model. We assess the performance of 3D-FFS on the KITTI dataset. Compared to F-ConvNet, we achieve improvements in training and inference times by up to 62.84 memory usage by up to 58.53 improvements in accuracy for the Car, Pedestrian and Cyclist classes, respectively. 3D-FFS shows a lot of promise in domains with limited computing power, such as autonomous vehicles, drones and robotics where LiDAR-Camera based sensor fusion perception systems are widely used.


page 1

page 3


PointPainting: Sequential Fusion for 3D Object Detection

Camera and lidar are important sensor modalities for robotics in general...

Design of Sensor Fusion Driver Assistance System for Active Pedestrian Safety

In this paper, we present a parallel architecture for a sensor fusion de...

Center Feature Fusion: Selective Multi-Sensor Fusion of Center-based Objects

Leveraging multi-modal fusion, especially between camera and LiDAR, has ...

Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles

Recent years have witnessed an increasing interest in improving the perc...

Sensor Adversarial Traits: Analyzing Robustness of 3D Object Detection Sensor Fusion Models

A critical aspect of autonomous vehicles (AVs) is the object detection s...

PointFusion: Deep Sensor Fusion for 3D Bounding Box Estimation

We present PointFusion, a generic 3D object detection method that levera...

GFD-SSD: Gated Fusion Double SSD for Multispectral Pedestrian Detection

Pedestrian detection is an essential task in autonomous driving research...

Please sign up or login with your details

Forgot password? Click here to reset