kevin-ssy/FishNet

Implementation code of the paper: FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction, NeurIPS 2018

41
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Emerging

This project offers a robust framework for advanced computer vision tasks, enabling accurate analysis of images for various predictions. It takes raw image data and processes it to identify objects, classify scenes, or segment specific regions, outputting highly precise predictions. This tool is for AI researchers and machine learning engineers who develop and deploy computer vision models.

545 stars. No commits in the last 6 months.

Use this if you need a high-performing and versatile deep learning backbone to build state-of-the-art image recognition, object detection, or semantic segmentation systems.

Not ideal if you are looking for a plug-and-play solution for general image editing or simple photo categorization without deep learning expertise.

image-recognition object-detection semantic-segmentation computer-vision deep-learning-research
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 23 / 25

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Stars

545

Forks

93

Language

Python

License

Last pushed

May 17, 2019

Commits (30d)

0

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