RefineNet download for Linux

This is the Linux app named RefineNet whose latest release can be downloaded as refinenetsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.

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RefineNet

DESCRIPTION:

RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. The repository supports both single-scale and multi-scale prediction, with scripts for training, testing, and evaluating segmentation performance. While this codebase is specific to MATLAB and MatConvNet, a PyTorch implementation and lighter-weight variants are also available from the community.

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• Implements RefineNet for high-resolution semantic segmentation
• Provides trained models on seven benchmark datasets
• Supports single-scale and multi-scale prediction with fusion
• Uses improved residual pooling for better segmentation accuracy
• Includes training and evaluation scripts for custom datasets
• Compatible with ResNet-101 and ResNet-152 backbones in MatConvNet

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C++, MATLAB, Python, Unix Shell

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This is an application that can also be fetched from https://sourceforge.net/projects/refinenet.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.