mlsanityData to 14 Oct 2026

CenterAtt: Fast 2-stage Center Attention Network

arXiv 2106.10493 ↗First posted 19 Jun 2021cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

In this technical report, we introduce the methods of HIKVISION_LiDAR_Det in the challenge of waymo open dataset real-time 3D detection. Our solution for the competition are built upon Centerpoint 3D detection framework. Several variants of CenterPoint are explored, including center attention head and feature pyramid network neck. In order to achieve real time detection, methods like batchnorm merge, half-precision floating point network and GPU-accelerated voxelization process are adopted. By using these methods, our team ranks 6th among all the methods on real-time 3D detection challenge in the waymo open dataset.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 3 of its 4 references that are in the map. First posted on arXiv 19 Jun 2021.

Builds on

3 of 4 references.

References · 3

  1. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  2. 2019Scalability in Perception for Autonomous Driving: Waymo Open Datasetcited by 2,451
  3. 2020Center-based 3D Object Detection and Trackingcited by 1,144

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Cited by year

Citing papers per year: 2021: 1; 2022: 3; 2023: 1.

5 papers.