# Holistic Parking Slot Detection with Polygon-Shaped Representations

arXiv: https://arxiv.org/abs/2310.11629 · HTML: https://mlsanity.com/paper/2310.11629/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 35 references that are in the map.
- First posted on arXiv 17 Oct 2023.

## Builds on (most cited first, 11 of 11)

- [YOLOv4: Optimal Speed and Accuracy of Object Detection](https://mlsanity.com/paper/2004.10934/) (2020)
- [Lift, Splat, Shoot: Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D](https://mlsanity.com/paper/2008.05711/) (2020)
- [Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression](https://mlsanity.com/paper/1911.08287/) (2019)
- [Cross-view Transformers for real-time Map-view Semantic Segmentation](https://mlsanity.com/paper/2205.02833/) (2022)
- [Simple-BEV: What Really Matters for Multi-Sensor BEV Perception?](https://mlsanity.com/paper/2206.07959/) (2022)
- [LaRa: Latents and Rays for Multi-Camera Bird's-Eye-View Semantic Segmentation](https://mlsanity.com/paper/2206.13294/) (2022)
- [Attentional Graph Neural Network for Parking-slot Detection](https://mlsanity.com/paper/2104.02576/) (2021)
- [PSDet: Efficient and Universal Parking Slot Detection](https://mlsanity.com/paper/2005.05528/) (2020)
- [End-to-End Trainable One-Stage Parking Slot Detection Integrating Global and Local Information](https://mlsanity.com/paper/2003.02445/) (2020)
- [CNN-based Two-Stage Parking Slot Detection Using Region-Specific Multi-Scale Feature Extraction](https://mlsanity.com/paper/2108.06185/) (2021)
- [Park4U Mate: Context-Aware Digital Assistant for Personalized Autonomous Parking](https://mlsanity.com/paper/2107.07851/) (2021)

## Built on by (most cited first, 2 of 2)

- [Enhanced Parking Perception by Multi-Task Fisheye Cross-view Transformers](https://mlsanity.com/paper/2408.12575/) (2024)
- [Click-Calib: A Robust Extrinsic Calibration Method for Surround-View Systems](https://mlsanity.com/paper/2501.01557/) (2025)

## Abstract (arXiv)

Current parking slot detection in advanced driver-assistance systems (ADAS) primarily relies on ultrasonic sensors. This method has several limitations such as the need to scan the entire parking slot before detecting it, the incapacity of detecting multiple slots in a row, and the difficulty of classifying them. Due to the complex visual environment, vehicles are equipped with surround view camera systems to detect vacant parking slots. Previous research works in this field mostly use image-domain models to solve the problem. These two-stage approaches separate the 2D detection and 3D pose estimation steps using camera calibration. In this paper, we propose one-step Holistic Parking Slot Network (HPS-Net), a tailor-made adaptation of the You Only Look Once (YOLO)v4 algorithm. This camera-based approach directly outputs the four vertex coordinates of the parking slot in topview domain, instead of a bounding box in raw camera images. Several visible points and shapes can be proposed from different angles. A novel regression loss function named polygon-corner Generalized Intersection over Union (GIoU) for polygon vertex position optimization is also proposed to manage the slot orientation and to distinguish the entrance line. Experiments show that HPS-Net can detect various vacant parking slots with a F1-score of 0.92 on our internal Valeo Parking Slots Dataset (VPSD) and 0.99 on the public dataset PS2.0. It provides a satisfying generalization and robustness in various parking scenarios, such as indoor (F1: 0.86) or paved ground (F1: 0.91). Moreover, it achieves a real-time detection speed of 17 FPS on Nvidia Drive AGX Xavier. A demo video can be found at https://streamable.com/75j7sj.