Pointillism

Author:

Bansal Kshitiz1,Rungta Keshav1,Zhu Siyuan1,Bharadia Dinesh1

Affiliation:

1. University of California San Diego

Publisher

ACM

Reference63 articles.

1. FMCW fundamentals in TI radar. https://training.ti.com/mmwave-training-series. FMCW fundamentals in TI radar. https://training.ti.com/mmwave-training-series.

2. Intel Real Sense D415 depth camera. https://www.intelrealsense.com/. Intel Real Sense D415 depth camera. https://www.intelrealsense.com/.

3. LiDAR vs. RADAR. https://www.sensorsmag.com/components/lidar-vs-radar. LiDAR vs. RADAR. https://www.sensorsmag.com/components/lidar-vs-radar.

4. OS-1 Ouster 16 channel LiDAR. https://ouster.com/products/os1-lidar-sensor/. OS-1 Ouster 16 channel LiDAR. https://ouster.com/products/os1-lidar-sensor/.

5. Perception matters: How deep learning enables autonomous vehicles to understand their environment. https://blogs.nvidia.com/blog/2018/08/10/autonomous-vehicles-perception-layer/. Perception matters: How deep learning enables autonomous vehicles to understand their environment. https://blogs.nvidia.com/blog/2018/08/10/autonomous-vehicles-perception-layer/.

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1. Enabling Visual Recognition at Radio Frequency;Proceedings of the 30th Annual International Conference on Mobile Computing and Networking;2024-05-29

2. Robust 3D Object Detection from LiDAR-Radar Point Clouds via Cross-Modal Feature Augmentation;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Enhancing mmWave Radar Point Cloud via Visual-inertial Supervision;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

4. Exploring Millimeter-Wave Radar Algorithms for Obstacle Detection and Tracking;2024 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC);2024-05-02

5. Automatic Multipath Annotation for Conventional Automotive Radar Datasets;IEEE Sensors Journal;2024-04-15

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