[IEEE T-PAMI] Awesome BEV perception research and cookbook for all level audience in autonomous diriving

TensorFlow Implementation for Computing a Semantically Segmented Bird's Eye View (BEV) Image Given the Images of Multiple Vehicle-Mounted Cameras.

[ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving

Talk2BEV: Language-Enhanced Bird's Eye View Maps (ICRA'24)

A ROS package for LiDAR's Bird's Eye View projection.

[ITSC 23] Official codebase for the paper 'Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion

PyTorch implementation of ComplexYOLO. This Repository is meant for students to learn object detection and working with LiDAR/RADAR datasets.

This repository is dedicated for 3D detection , sensor fusion and tracking using camera and LIDAR data

example of homography camera displacement

Birds-Eye view of a car and its surroundings for park assist.

Transforming multiple vehicle-mounted camera images into a bird’s-eye view (BEV), this project employs deep learning, including a U-Net backbone for semantic segmentation and a spatial transformer module.

A dashboard for monitoring 1 meter social distancing for outdoor areas using computer vision

The code used by the team of the Hanze UAS during the Self Driving Challenge 2024

In this project, the aim is denoting danger zones for suspended loads and creating warnings for workers inside these danger zones. Overall pipeline consists of object detection, object tracking and distance estimation by using bird’s eye view transformation.

Perspective transformation (birds eye) tool, for easy experimenting and finding the right transformation values.

Made a social distance monitoring system and a Spit Detection system in python.

🔦 Searchlight is a bird's-eye view video game inspired by MoPOP located in Seattle. The player has to track down the listed targets in the dark, with only a short-range flashlight.

Geo-trax is a comprehensive pipeline for extracting and analyzing high-accuracy georeferenced vehicle trajectories from quasi-stationary, bird’s-eye view drone footage. Using advanced computer vision and deep learning, it enables detailed urban traffic analysis and supports scalable, precise studies of vehicle dynamics.

🗺️ Create landscape design images in bird's eye view using DALL-E 3.