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Found 6 papers, 4 papers with code
CenterNet3D: An Anchor Free Object Detector for Point Cloud
However, because inherent sparsity of point clouds, 3D object center points are likely to be in empty space which makes it difficult to estimate accurate boundaries.
Comparison of Different Methods for Time Sequence Prediction in Autonomous Vehicles
As a combination of various kinds of technologies, autonomous vehicles could complete a series of driving tasks by itself, such as perception, decision-making, planning, and control.
Multi-View Adaptive Fusion Network for 3D Object Detection
3D object detection based on LiDAR-camera fusion is becoming an emerging research theme for autonomous driving.
FII-CenterNet: An Anchor-Free Detector With Foreground Attention for Traffic Object Detection
Most successful object detectors are anchor-based, which is difficult to adapt to the diversity of traffic objects.
AutoMine: An Unmanned Mine Dataset
The main contributions of the AutoMine dataset are as follows: 1. The first autonomous driving dataset for perception and localization in mine scenarios.
Point Cloud Classification Using Content-based Transformer via Clustering in Feature Space
To overcome the limitation of local spatial attention, we propose a point content-based Transformer architecture, called PointConT for short.
Ranked #9 on
3D Point Cloud Classification
on ScanObjectNN
