Search Results for author: Mohamed Shawky

Found 1 papers, 0 papers with code

Unsupervised Neural Sensor Models for Synthetic LiDAR Data Augmentation

no code implementations24 Nov 2019 Ahmad El Sallab, Ibrahim Sobh, Mohamed Zahran, Mohamed Shawky

Evaluation is performed on unseen real LiDAR frames from KITTI dataset, with different amounts of simulated data augmentation using the two proposed approaches, showing improvement of 6% mAP for the object detection task, in favor of the augmenting LiDAR point clouds adapted with the proposed neural sensor models over the raw simulated LiDAR.

Data Augmentation object-detection +2

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