KyujinHan/Object-Depth-detection-based-hybrid-Distance-estimator
We use our VDEmodel. Our purpose is that predict the distance between car based on Deep-Learning.
This project helps automotive engineers and ADAS developers accurately estimate the distance to other vehicles using just a single camera. By inputting images or video frames from a car's monocular camera, it outputs precise distance predictions. This is crucial for developing and enhancing advanced driver assistance systems that rely on understanding the car's surroundings.
No commits in the last 6 months.
Use this if you need to integrate a reliable, deep learning-based solution for vehicle distance estimation into your advanced driver assistance systems (ADAS) using only monocular camera feeds.
Not ideal if you require distance measurements from stereo cameras, LiDAR, or radar, or if your primary focus is on object detection without specific distance quantification.
Stars
18
Forks
3
Language
Jupyter Notebook
License
—
Category
Last pushed
Oct 09, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/KyujinHan/Object-Depth-detection-based-hybrid-Distance-estimator"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
vita-epfl/monoloco
A 3D vision library from 2D keypoints: monocular and stereo 3D detection for humans, social...
fangchangma/self-supervised-depth-completion
ICRA 2019 "Self-supervised Sparse-to-Dense: Self-supervised Depth Completion from LiDAR and...
nburrus/stereodemo
Small Python utility to compare and visualize the output of various stereo depth estimation algorithms
JiawangBian/sc_depth_pl
SC-Depth (V1, V2, and V3) for Unsupervised Monocular Depth Estimation ...
wvangansbeke/Sparse-Depth-Completion
Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st...