# TetraPackNet: Four-Corner-Based Object Detection in Logistics Use-Cases

arXiv: https://arxiv.org/abs/2104.09123 · HTML: https://mlsanity.com/paper/2104.09123/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 17 references that are in the map.
- First posted on arXiv 19 Apr 2021.

## Builds on (most cited first, 14 of 14)

- [Microsoft COCO: Common Objects in Context](https://mlsanity.com/paper/1405.0312/) (2014)
- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning](https://mlsanity.com/paper/1602.07261/) (2016)
- [Objects as Points](https://mlsanity.com/paper/1904.07850/) (2019)
- [Stacked Hourglass Networks for Human Pose Estimation](https://mlsanity.com/paper/1603.06937/) (2016)
- [CornerNet: Detecting Objects as Paired Keypoints](https://mlsanity.com/paper/1808.01244/) (2018)
- [CenterNet: Keypoint Triplets for Object Detection](https://mlsanity.com/paper/1904.08189/) (2019)
- [Deep Learning for Generic Object Detection: A Survey](https://mlsanity.com/paper/1809.02165/) (2018)
- [Associative Embedding: End-to-End Learning for Joint Detection and Grouping](https://mlsanity.com/paper/1611.05424/) (2016)
- [Recent Advances in Deep Learning for Object Detection](https://mlsanity.com/paper/1908.03673/) (2019)
- [CornerNet-Lite: Efficient Keypoint Based Object Detection](https://mlsanity.com/paper/1904.08900/) (2019)
- [Deep Cuboid Detection: Beyond 2D Bounding Boxes](https://mlsanity.com/paper/1611.10010/) (2016)
- [Fully-Automated Packaging Structure Recognition in Logistics Environments](https://mlsanity.com/paper/2008.04620/) (2020)
- [An Image Processing Pipeline for Automated Packaging Structure Recognition](https://mlsanity.com/paper/2009.13824/) (2020)

## Built on by (most cited first, 6 of 6)

- [Literature Review: Computer Vision Applications in Transportation Logistics and Warehousing](https://mlsanity.com/paper/2304.06009/) (2023)
- [Scrape, Cut, Paste and Learn: Automated Dataset Generation Applied to Parcel Logistics](https://mlsanity.com/paper/2210.09814/) (2022)
- [Parcel3D: Shape Reconstruction from Single RGB Images for Applications in Transportation Logistics](https://mlsanity.com/paper/2304.08994/) (2023)
- [Patterns of Vehicle Lights: Addressing Complexities in Curation and Annotation of Camera-Based Vehicle Light Datasets and Metrics](https://mlsanity.com/paper/2307.14521/) (2023)
- [TAMPAR: Visual Tampering Detection for Parcel Logistics in Postal Supply Chains](https://mlsanity.com/paper/2311.03124/) (2023)
- [Robust Detection, Association, and Localization of Vehicle Lights: A Context-Based Cascaded CNN Approach and Evaluations](https://mlsanity.com/paper/2307.14571/) (2023)

## Abstract (arXiv)

While common image object detection tasks focus on bounding boxes or segmentation masks as object representations, we consider the problem of finding objects based on four arbitrary vertices. We propose a novel model, named TetraPackNet, to tackle this problem. TetraPackNet is based on CornerNet and uses similar algorithms and ideas. It is designated for applications requiring high-accuracy detection of regularly shaped objects, which is the case in the logistics use-case of packaging structure recognition. We evaluate our model on our specific real-world dataset for this use-case. Baselined against a previous solution, consisting of a Mask R-CNN model and suitable post-processing steps, TetraPackNet achieves superior results (9% higher in accuracy) in the sub-task of four-corner based transport unit side detection.