8 citations · 8 across the 5 of their papers we have counts for
4 papers · 1 filter
Leveraging Pre-Trained 3D Object Detection Models For Fast Ground Truth Generation
Jungwook Lee, Sean Walsh, Ali Harakeh +1
Training 3D object detectors for autonomous driving has been limited to small datasets due to the effort required to generate annotations. Reducing both task complexity and the amo…
Unlimited Road-scene Synthetic Annotation (URSA) Dataset
Matt Angus, Mohamed ElBalkini, Samin Khan +5
In training deep neural networks for semantic segmentation, the main limiting factor is the low amount of ground truth annotation data that is available in currently existing datas…
A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detection
Alex D. Pon, Oles Andrienko, Ali Harakeh +1
Traffic light and sign detectors on autonomous cars are integral for road scene perception. The literature is abundant with deep learning networks that detect either lights or sign…
In Defense of Classical Image Processing: Fast Depth Completion on the CPU
Jason Ku, Ali Harakeh, Steven L. Waslander
With the rise of data driven deep neural networks as a realization of universal function approximators, most research on computer vision problems has moved away from hand crafted c…