haochange / DUpsampling

This repo is an pytorch implementation of CVPR2019 paper: Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation

DUpsampling

This repo is an unofficial pytorch implementation of CVPR19 paper: Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation: https://arxiv.org/abs/1903.02120

Installation

• pytorch==0.4.1
• python==3.5
• numpy
• torchvision
• matplotlib
• opencv-python
• dominate
• random
• collections
• shutil

Dataset and pretrained model

Plesae download VOC12_aug dataset and unzip the dataset into data, and modify your configuration in options/base options.py.

Usage

bash train.sh

Segmentation results on val set

To do

• Add softmax with temperature
• Modify the network and improve the accuracy

under construction...

If you have any question, feel free to contact me or submit issue.