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Found 7 papers, 3 papers with code
Label-Efficient 3D Object Detection For Road-Side Units
We address this challenge by devising a label-efficient object detection method for RSU based on unsupervised object discovery.
Practical Collaborative Perception: A Framework for Asynchronous and Multi-Agent 3D Object Detection
In this work, we devise a simple yet effective collaboration method that achieves a better bandwidth-performance tradeoff than prior state-of-the-art methods while minimizing changes made to the single-vehicle detection models and relaxing unrealistic assumptions on inter-agent synchronization.
Aligning Bird-Eye View Representation of Point Cloud Sequences using Scene Flow
Such concatenation is possible thanks to the removal of ego vehicle motion using its odometry.
Attention-based Proposals Refinement for 3D Object Detection
This paper proposes a data-driven approach to ROI feature computing named APRO3D-Net which consists of a voxel-based RPN and a refinement stage made of Vector Attention.
A two-stage data association approach for 3D Multi-object Tracking
Multi-object tracking (MOT) is an integral part of any autonomous driving pipelines because itproduces trajectories which has been taken by other moving objects in the scene and helps predicttheir future motion.
R-AGNO-RPN: A LIDAR-Camera Region Deep Network for Resolution-Agnostic Detection
In this paper, R-AGNO-RPN, a region proposal network built on fusion of 3D point clouds and RGB images is proposed for 3D object detection regardless of point cloud resolution.
Vision-Based Road Detection using Contextual Blocks
Our starting point is the well-known machine learning approach, in which a classifier is trained to distinguish road and non-road regions based on hand-labeled images.
