mlsanityData to 7 Oct 2026

Literature Review: Computer Vision Applications in Transportation Logistics and Warehousing

arXiv 2304.06009 ↗First posted 12 Apr 2023cs.CV cs.LGcited by 5

Not on the map. Why?

Abstract (arXiv)

Computer vision applications in transportation logistics and warehousing have a huge potential for process automation. We present a structured literature review on research in the field to help leverage this potential. The literature is categorized w.r.t. the application, i.e. the task it tackles and w.r.t. the computer vision techniques that are used. Regarding applications, we subdivide the literature in two areas: Monitoring, i.e. observing and retrieving relevant information from the environment, and manipulation, where approaches are used to analyze and interact with the environment. Additionally, we point out directions for future research and link to recent developments in computer vision that are suitable for application in logistics. Finally, we present an overview of existing datasets and industrial solutions. The results of our analysis are also available online at https://a-nau.github.io/cv-in-logistics.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 45 of its 162 references that are in the map. First posted on arXiv 12 Apr 2023.

Builds on

45 of 162 references.

References · 45

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2015Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networkscited by 9,617
  4. 2017Mask R-CNNcited by 7,259
  5. 2016Feature Pyramid Networks for Object Detectioncited by 5,021
  6. 2021SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformerscited by 2,923
  7. 2018YOLOv3: An Incremental Improvementcited by 2,652
  8. 2019SuperGlue: Learning Feature Matching with Graph Neural Networkscited by 1,437
  9. 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,064
  10. 2018CornerNet: Detecting Objects as Paired Keypointscited by 763
  11. 2020Image Segmentation Using Deep Learning: A Surveycited by 659
  12. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
33 more
  1. 2020Deep Learning for Person Re-identification: A Survey and Outlookcited by 547
  2. 2019Object Detection in 20 Years: A Surveycited by 528
  3. 2018Object Detection with Deep Learning: A Reviewcited by 524
  4. 2017Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)cited by 472
  5. 2017Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detectioncited by 209
  6. 2022Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wildcited by 159
  7. 2019Learning Object Bounding Boxes for 3D Instance Segmentation on Point Cloudscited by 156
  8. 2022DiT: Self-supervised Pre-training for Document Image Transformercited by 152
  9. 2020RTM3D: Real-time Monocular 3D Detection from Object Keypoints for Autonomous Drivingcited by 150
  10. 2018PlaneRCNN: 3D Plane Detection and Reconstruction from a Single Imagecited by 105
  11. 2019Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detectioncited by 104
  12. 2018CubeSLAM: Monocular 3D Object SLAMcited by 101
  13. 2016Multi-view Self-supervised Deep Learning for 6D Pose Estimation in the Amazon Picking Challengecited by 70
  14. 2020Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)cited by 56
  15. 2016Analysis and Observations from the First Amazon Picking Challengecited by 41
  16. 2021DocTr: Document Image Transformer for Geometric Unwarping and Illumination Correctioncited by 38
  17. 2019A survey of advances in vision-based vehicle re-identificationcited by 36
  18. 2015A Dataset for Improved RGBD-based Object Detection and Pose Estimation for Warehouse Pick-and-Placecited by 35
  19. 2020A Survey of Deep Learning Approaches for OCR and Document Understandingcited by 32
  20. 2020Review: deep learning on 3D point cloudscited by 29
  21. 2022Revisiting Document Image Dewarping by Grid Regularizationcited by 24
  22. 2022Fourier Document Restoration for Robust Document Dewarping and Recognitioncited by 21
  23. 2021Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Networkcited by 20
  24. 2020Can You Read Me Now? Content Aware Rectification using Angle Supervisioncited by 18
  25. 2022UDoc-GAN: Unpaired Document Illumination Correction with Background Light Priorcited by 15
  26. 2018Detection, localisation and tracking of pallets using machine learning techniques and 2D range datacited by 10
  27. 2020Fully-Automated Packaging Structure Recognition in Logistics Environmentscited by 6
  28. 2021TetraPackNet: Four-Corner-Based Object Detection in Logistics Use-Casescited by 6
  29. 2019Geometry-constrained Car Recognition Using a 3D Perspective Networkcited by 5
  30. 2020Refined Plane Segmentation for Cuboid-Shaped Objects by Leveraging Edge Detectioncited by 5
  31. 2022Scrape, Cut, Paste and Learn: Automated Dataset Generation Applied to Parcel Logisticscited by 4
  32. 2018KittingBot: A Mobile Manipulation Robot for Collaborative Kitting in Automotive Logisticscited by 2
  33. 2019Classifying logistic vehicles in cities using Deep learningcited by 1

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 1; 2025: 1.

5 papers.

  1. 2023Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaulcited by 4
  2. 2024Industrial Language-Image Dataset (ILID): Adapting Vision Foundation Models for Industrial Settingscited by 4
  3. 2023Parcel3D: Shape Reconstruction from Single RGB Images for Applications in Transportation Logisticscited by 1
  4. 2023TAMPAR: Visual Tampering Detection for Parcel Logistics in Postal Supply Chainscited by 1
  5. 2025The Impact of Synthetic Data on Object Detection Model Performance: A Comparative Analysis with Real-World Datacited by 1