mlsanityData to 14 Oct 2026

Survey and Systematization of 3D Object Detection Models and Methods

arXiv 2201.09354 ↗First posted 23 Jan 2022cs.CV cs.AI cs.LGcited by 3

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Abstract (arXiv)

Strong demand for autonomous vehicles and the wide availability of 3D sensors are continuously fueling the proposal of novel methods for 3D object detection. In this paper, we provide a comprehensive survey of recent developments from 2012-2021 in 3D object detection covering the full pipeline from input data, over data representation and feature extraction to the actual detection modules. We introduce fundamental concepts, focus on a broad range of different approaches that have emerged over the past decade, and propose a systematization that provides a practical framework for comparing these approaches with the goal of guiding future development, evaluation and application activities. Specifically, our survey and systematization of 3D object detection models and methods can help researchers and practitioners to get a quick overview of the field by decomposing 3DOD solutions into more manageable pieces.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 105 of its 182 references that are in the map. First posted on arXiv 23 Jan 2022.

Builds on

105 of 182 references.

References · 105

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38 more
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50 most cited of 105 All 105 (JSON)

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Cited by year

Citing papers per year: 2023: 1; 2024: 0; 2025: 2.

3 papers.

  1. 2023LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusioncited by 58
  2. 2025Hi-ALPS -- An Experimental Robustness Quantification of Six LiDAR-based Object Detection Systems for Autonomous Drivingcited by 0
  3. 2025WLTCL: Wide Field-of-View 3-D LiDAR Truck Compartment Automatic Localization Systemcited by 0