chaytonmin/Awesome-BEV-Perception-Multi-Cameras
A curated collection of papers on bird's-eye-view perception and 3D object detection using deep learning models from multi-camera inputs.
Not currently ranked — collecting fresh signals.
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This repository aggregates academic papers on bird’s-eye-view (BEV) perception for autonomous vehicles, covering multi-camera 3D object detection and segmentation models. It includes implementations of transformer-based approaches like BEVFormer and DETR3D, as well as depth estimation methods like BEVDepth. The papers span venues including CVPR, ICCV, and ECCV, representing state-of-the-art computer vision research for perception in self-driving systems.
Frequently asked
- What is chaytonmin/Awesome-BEV-Perception-Multi-Cameras?
- A curated collection of papers on bird's-eye-view perception and 3D object detection using deep learning models from multi-camera inputs.
- Is Awesome-BEV-Perception-Multi-Cameras open source?
- Yes — chaytonmin/Awesome-BEV-Perception-Multi-Cameras is an open-source project tracked on heatdrop.
- How popular is Awesome-BEV-Perception-Multi-Cameras?
- chaytonmin/Awesome-BEV-Perception-Multi-Cameras has 1.1k stars on GitHub.
- Where can I find Awesome-BEV-Perception-Multi-Cameras?
- chaytonmin/Awesome-BEV-Perception-Multi-Cameras is on GitHub at https://github.com/chaytonmin/Awesome-BEV-Perception-Multi-Cameras.