TANet: Robust 3D Object Detection from Point Clouds with Triple Attention

12/11/2019
by   Zhe Liu, et al.
0

In this paper, we focus on exploring the robustness of the 3D object detection in point clouds, which has been rarely discussed in existing approaches. We observe two crucial phenomena: 1) the detection accuracy of the hard objects, e.g., Pedestrians, is unsatisfactory, 2) when adding additional noise points, the performance of existing approaches decreases rapidly. To alleviate these problems, a novel TANet is introduced in this paper, which mainly contains a Triple Attention (TA) module, and a Coarse-to-Fine Regression (CFR) module. By considering the channel-wise, point-wise and voxel-wise attention jointly, the TA module enhances the crucial information of the target while suppresses the unstable cloud points. Besides, the novel stacked TA further exploits the multi-level feature attention. In addition, the CFR module boosts the accuracy of localization without excessive computation cost. Experimental results on the validation set of KITTI dataset demonstrate that, in the challenging noisy cases, i.e., adding additional random noisy points around each object,the presented approach goes far beyond state-of-the-art approaches. Furthermore, for the 3D object detection task of the KITTI benchmark, our approach ranks the first place on Pedestrian class, by using the point clouds as the only input. The running speed is around 29 frames per second.

READ FULL TEXT

page 1

page 7

page 9

research
12/31/2021

PiFeNet: Pillar-Feature Network for Real-Time 3D Pedestrian Detection from Point Cloud

We present PiFeNet, an efficient and accurate real-time 3D detector for ...
research
06/26/2021

TANet++: Triple Attention Network with Filtered Pointcloud on 3D Detection

TANet is one of state-of-the-art 3D object detection method on KITTI and...
research
06/07/2020

SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds

Accurate 3D object detection from point clouds has become a crucial comp...
research
10/10/2021

3D Object Detection Combining Semantic and Geometric Features from Point Clouds

In this paper, we investigate the combination of voxel-based methods and...
research
10/21/2021

A Fast Location Algorithm for Very Sparse Point Clouds Based on Object Detection

Limited by the performance factor, it is arduous to recognize target obj...
research
02/13/2023

Surface-biased Multi-Level Context 3D Object Detection

Object detection in 3D point clouds is a crucial task in a range of comp...
research
10/12/2021

Improved Pillar with Fine-grained Feature for 3D Object Detection

3D object detection with LiDAR point clouds plays an important role in a...

Please sign up or login with your details

Forgot password? Click here to reset