Learning to Simulate Realistic LiDARs

Author:

Guillard Benoit1,Vemprala Sai2,Gupta Jayesh K.2,Miksik Ondrej3,Vineet Vibhav2,Fua Pascal1,Kapoor Ashish2

Affiliation:

1. École polytechnique fédérale de Lausanne,Lausanne,Switzerland

2. Microsoft Research,Redmond,USA

3. Microsoft Mixed Reality & AI Lab,Zurich,Switzerland

Publisher

IEEE

Reference37 articles.

1. End-to-end sensor modeling for LiDAR Point Cloud

2. Adam: A method for stochastic gradient descent;kingma;International Conference on Learning Representations (ICLR),0

3. Learning to Predict Lidar Intensities

4. Instance normalization: The missing ingredient for fast stylization;ulyanov;ArXiv Preprint,2016

5. Simulated Intensity Rendering of 3D Li-DAR using Generative Adversarial Network;mok;IEEE International Conference on Big Data and Smart Computing (BigComp),0

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3. Neural LiDAR Fields for Novel View Synthesis;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

4. Towards Zero Domain Gap: A Comprehensive Study of Realistic LiDAR Simulation for Autonomy Testing;2023 IEEE/CVF International Conference on Computer Vision (ICCV);2023-10-01

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