SPP-Net
A re-implementation of the SPP-net object detection algorithm using spatial pyramid pooling in deep convolutional networks for visual recognition.
What is SPP-Net?
SPP-net is a re-implementation of the spatial pyramid pooling algorithm for deep convolutional networks, designed for visual recognition tasks like object detection. It solves the problem of fixed-size input constraints in traditional CNNs by allowing networks to process images of arbitrary dimensions through pyramid pooling layers. The implementation reproduces the results from the original ECCV 2014 research paper.
Computer vision researchers and developers working on object detection and visual recognition systems, particularly those needing to implement or experiment with spatial pyramid pooling techniques.
Developers choose SPP-net because it provides a faithful, working implementation of the influential SPP-net paper with complete training and detection pipelines. It offers practical tools for reproducing research results and building upon the spatial pyramid pooling approach.
Overview
SPP_net : Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Use Cases
Best For
- Implementing spatial pyramid pooling in convolutional neural networks
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
