prstrive/EPCDepth
[ICCV 2021] Excavating the Potential Capacity of Self-Supervised Monocular Depth Estimation
This project helps self-driving car engineers and robotics researchers create accurate 3D spatial awareness from standard camera images. It takes a single image from a moving vehicle's camera and estimates the distance of every pixel, producing a depth map (disparity map). This is particularly useful for tasks like obstacle detection and path planning in autonomous systems.
129 stars. No commits in the last 6 months.
Use this if you need to generate highly accurate depth information from single camera images for autonomous vehicles or robotic navigation, especially when dealing with complex scenes and occlusions.
Not ideal if you require real-time processing on embedded systems with limited computational resources, or if you primarily work with datasets other than KITTI or NYUv2 without extensive adaptation.
Stars
129
Forks
18
Language
Python
License
MIT
Category
Last pushed
Oct 17, 2021
Commits (30d)
0
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