mlsanityData to 14 Oct 2026

Deep Perspective Transformation Based Vehicle Localization on Bird's Eye View

arXiv 2311.06796 ↗First posted 12 Nov 2023cs.CVcited by 0

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Abstract (arXiv)

An accurate understanding of a self-driving vehicle's surrounding environment is crucial for its navigation system. To enhance the effectiveness of existing algorithms and facilitate further research, it is essential to provide comprehensive data to the routing system. Traditional approaches rely on installing multiple sensors to simulate the environment, leading to high costs and complexity. In this paper, we propose an alternative solution by generating a top-down representation of the scene, enabling the extraction of distances and directions of other cars relative to the ego vehicle. We introduce a new synthesized dataset that offers extensive information about the ego vehicle and its environment in each frame, providing valuable resources for similar downstream tasks. Additionally, we present an architecture that transforms perspective view RGB images into bird's-eye-view maps with segmented surrounding vehicles. This approach offers an efficient and cost-effective method for capturing crucial environmental information for self-driving cars. Code and dataset are available at https://github.com/IPM-HPC/Perspective-BEV-Transformer.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 22 of its 29 references that are in the map. First posted on arXiv 12 Nov 2023.

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22 of 29 references.

References · 22

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10 more
  1. 2018Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networkscited by 84
  2. 2020A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird's Eye Viewcited by 72
  3. 2020FISHING Net: Future Inference of Semantic Heatmaps In Gridscited by 55
  4. 2021Bird's-Eye-View Panoptic Segmentation Using Monocular Frontal View Imagescited by 48
  5. 2018Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systemscited by 42
  6. 2018Generative Adversarial Frontal View to Bird View Synthesiscited by 25
  7. 2022Homography Loss for Monocular 3D Object Detectioncited by 24
  8. 2017Learning to Map Vehicles into Bird's Eye Viewcited by 12
  9. 2019Short-Term Prediction and Multi-Camera Fusion on Semantic Gridscited by 4
  10. 2022Autonomous Vehicles: Open-Source Technologies, Considerations, and Developmentcited by 2

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