• Corpus ID: 214151340

Scalability in Perception for Autonomous Driving: An Open Dataset Benchmark

@inproceedings{Sun2019ScalabilityIP,
  title={Scalability in Perception for Autonomous Driving: An Open Dataset Benchmark},
  author={Pei Sun and Henrik Kretzschmar and Xerxes Dotiwalla and Aurelien Chouard and Vijaysai Patnaik and Paul Tsui and James Guo and Yin Zhou and Yuning Chai and Benjamin Caine and Vijay Vasudevan and Wei Han and Jiquan Ngiam and Hang Zhao and Aleksei Timofeev and Scott M. Ettinger and Maxim Krivokon and Amy Gao and Aditya Joshi and Yuzhang and Jonathon Shlens and Z. Chen and Dragomir Anguelov},
  year={2019}
}
Simulating the Autonomous Future: A Look at Virtual Vehicle Environments and How to Validate Simulation Using Public Data Sets
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A proposed framework for constructing, parameterizing, and validating a virtual vehicle environment using an existing AV data set is examined, including an overview of several open source and commercially available simulation tools for scene and scenario creation.
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3D Object Detection with Enriched Point Cloud
  • Dazhi Cheng
  • Computer Science, Environmental Science
  • 2020
TLDR
This thesis proposes a multi-view segmentationdetection fusion framework that enhances metric-preserving yet sparse voxel feature learning by dense observations from perspective view and significantly boosts performance of state-of-the-art detectors by introducing multiple points per beam.
ECP2.5D - Person Localization in Traffic Scenes
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The recently released EuroCity Persons detection dataset is enhanced, a large and diverse automotive dataset covering pedestrians and riders, and an automatic 3D lifting procedure is introduced by using additional LiDAR distance measurements to augment a large part of the reasonable subset of 2D box annotations with their corresponding 3D point positions.
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