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Mar 3, 2019 · This paper proposes an on-road object detection method, which uses 3D information acquired by a LiDAR HD sensor.
On-road object detection is one of the main topics in the development of autonomous vehicles. Factors related to the diversity of classes, pose changes, ...
To carry this out, a multi-resolution conditioning stage is proposed in order to optimize the performance of the PointNet architecture applied over LiDAR data.
To carry this out, a multi-resolution conditioning stage is proposed in order to optimize the performance of the PointNet architecture applied over LiDAR data.
Pointnet evaluation for on-road object detection using a multi-resolution conditioning ; QRCode ; Compartir ; Fecha. 2019 ; Autor(es). Pamplona J. · Madrigal C. · de ...
Pointnet evaluation for on-road object detection using a multi-resolution conditioning ; dc.contributor.author, Pamplona J. ; dc.contributor.author, Madrigal C.
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Secondly, the original model of PointNet gets 93.47% accuracy on the same dataset. On the other hand, the evaluation of our model shows an accuracy of 90.43% ...
Oct 22, 2024 · We evaluate a neural network architecture based on PointNet for multi-resolution 3D objects. To carry this out, a multi-resolution conditioning ...
We propose PointStack, a novel point cloud feature learning network that utilizes multi-resolution feature learning and learnable pooling (LP).
Missing: Road Conditioning.