MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time

06/29/2020
by   Xichuan Zhou, et al.
0

Monocular multi-object detection and localization in 3D space has been proven to be a challenging task. The MoNet3D algorithm is a novel and effective framework that can predict the 3D position of each object in a monocular image and draw a 3D bounding box for each object. The MoNet3D method incorporates prior knowledge of the spatial geometric correlation of neighbouring objects into the deep neural network training process to improve the accuracy of 3D object localization. Experiments on the KITTI dataset show that the accuracy for predicting the depth and horizontal coordinates of objects in 3D space can reach 96.25% and 94.74%, respectively. Moreover, the method can realize the real-time image processing at 27.85 FPS, showing promising potential for embedded advanced driving-assistance system applications. Our code is publicly available at https://github.com/CQUlearningsystemgroup/YicongPeng.

READ FULL TEXT

page 3

page 6

research
01/10/2020

RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Driving

In this work, we propose an efficient and accurate monocular 3D detectio...
research
03/30/2021

Delving into Localization Errors for Monocular 3D Object Detection

Estimating 3D bounding boxes from monocular images is an essential compo...
research
12/22/2022

Monocular 3D Object Detection using Multi-Stage Approaches with Attention and Slicing aided hyper inference

3D object detection is vital as it would enable us to capture objects' s...
research
07/20/2022

An Embedded Monocular Vision Approach for Ground-Aware Objects Detection and Position Estimation

In the RoboCup Small Size League (SSL), teams are encouraged to propose ...
research
08/12/2021

Progressive Coordinate Transforms for Monocular 3D Object Detection

Recognizing and localizing objects in the 3D space is a crucial ability ...
research
05/22/2023

nnDetection for Intracranial Aneurysms Detection and Localization

Intracranial aneurysms are a commonly occurring and life-threatening con...
research
05/13/2018

LMNet: Real-time Multiclass Object Detection on CPU using 3D LiDARs

This paper describes an optimized single-stage deep convolutional neural...

Please sign up or login with your details

Forgot password? Click here to reset