aayushbansal/PixelNet
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at
This project offers an architecture for pixel-level prediction problems, improving the efficiency and accuracy of tasks like image segmentation and object detection. It takes in raw image data and outputs detailed pixel-level classifications or estimations, such as identifying object boundaries or surface normals. Researchers and engineers working in computer vision or image processing would find this useful for developing advanced image analysis applications.
197 stars. No commits in the last 6 months.
Use this if you are a computer vision researcher or practitioner looking to train highly accurate models for detailed pixel-level tasks like semantic segmentation or surface normal estimation, even with limited data.
Not ideal if you need a plug-and-play solution for general image classification or object detection without delving into the underlying model architecture and training process.
Stars
197
Forks
48
Language
Matlab
License
MIT
Category
Last pushed
Jun 08, 2017
Commits (30d)
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