Search Results for author:
Found 6 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.
3D-FlowNet: Event-based optical flow estimation with 3D representation
Event-based cameras can overpass frame-based cameras limitations for important tasks such as high-speed motion detection during self-driving cars navigation in low illumination conditions.
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.
