Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object Detection-Reference-Cited by-同舟云学术

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Fine-Grained Pillar Feature Encoding Via Spatio-Temporal Virtual Grid for 3D Object Detection

Published:2024-05-13 Issue: Volume:30 Page:4259-4265
ISSN:
Container-title:2024 IEEE International Conference on Robotics and Automation (ICRA)
language:
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Author:

Park Konyul¹,Kim Yecheol²,Koh Junho²,Park Byungwoo¹,Choi Jun Won³

Affiliation:

1. Hanyang University,Department of Artificial Intelligence,Seoul,Korea,04763

2. Hanyang University,Department of Electrical Engineering,Seoul,Korea,04763

3. Seoul National University,College of Liberal Studies,Department of Electrical and Computer Engineering,Seoul,Korea,08826

Funder

National Research Foundation of Korea

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10609961/10609862/10611414.pdf?arnumber=10611414

Reference27 articles.

1. Center-based 3D Object Detection and Tracking

2. PointPillars: Fast Encoders for Object Detection From Point Clouds

3. PillarNet: Real-Time and High-Performance Pillar-Based 3D Object Detection

4. VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

5. SECOND: Sparsely Embedded Convolutional Detection

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