FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery (TGRS)

Last update: Jan 05, 2023

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Deep Learning FactSeg

Overview

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery

by Ailong Ma, Junjue Wang, Yanfei Zhong and Zhuo Zheng

This is an official implementation of FactSeg in our TGRS paper " FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery "

Citation

If you use FactSeg in your research, please cite our coming TGRS paper.

@ARTICLE{FactSeg,
  author={Ma Ailong, Wang Junjue, Zhong Yanfei and Zheng Zhuo},
  journal={IEEE Transactions on Geoscience and Remote Sensing}, 
  title={FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery}, 
  year={2021},
  volume={},
  number={},
  pages={1-16},
  doi={10.1109/TGRS.2021.3097148}}

This is follow-up work of our FarSeg (CVPR2020).

@inproceedings{zheng2020foreground,
  title={Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery},
  author={Zheng, Zhuo and Zhong, Yanfei and Wang, Junjue and Ma, Ailong},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={4096--4105},
  year={2020}
}

Getting Started

Install SimpleCV

pip install --upgrade git+https://github.com/Z-Zheng/SimpleCV.git

Requirements:

pytorch >= 1.1.0
python >=3.6

Prepare iSAID Dataset

ln -s </path/to/iSAID> ./isaid_segm

Evaluate Model

1. download pretrained weight in Google Drive

2. move weight file to log directory

mkdir -vp ./log/
mv ./factseg50.pth ./log/model-60000.pth

3. inference on iSAID val

bash ./scripts/eval_factseg.sh

Train Model

bash ./scripts/train_factseg.sh

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery (TGRS)

Related tags

Overview

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery

by Ailong Ma, Junjue Wang, Yanfei Zhong and Zhuo Zheng

Citation

Getting Started

Install SimpleCV

Requirements:

Prepare iSAID Dataset

Evaluate Model

1. download pretrained weight in Google Drive

2. move weight file to log directory

3. inference on iSAID val

Train Model

Owner

Kingdrone

Github for the conference paper GLOD-Gaussian Likelihood OOD detector

Open source repository for the code accompanying the paper 'PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations'.

Code for "Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo"

Cooperative Driving Dataset: a dataset for multi-agent driving scenarios

How the Deep Q-learning method works and discuss the new ideas that makes the algorithm work

Code for Boundary-Aware Segmentation Network for Mobile and Web Applications

Deep Markov Factor Analysis (NeurIPS2021)

This is an implementation of PIFuhd based on Pytorch

Repository containing the PhD Thesis "Formal Verification of Deep Reinforcement Learning Agents"

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Machine Learning in Asset Management (by @firmai)

Dynamic Bottleneck for Robust Self-Supervised Exploration

A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM's

Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"

Unity Propagation in Bayesian Networks Handling Inconsistency via Unity Smoothing

Run Keras models in the browser, with GPU support using WebGL

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Detector for Log4Shell exploitation attempts

It's a powerful version of linebot

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN)

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery (TGRS)

Related tags

Overview

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery

by Ailong Ma, Junjue Wang*, Yanfei Zhong* and Zhuo Zheng

Citation

Getting Started

Install SimpleCV

Requirements:

Prepare iSAID Dataset

Evaluate Model

1. download pretrained weight in Google Drive

2. move weight file to log directory

3. inference on iSAID val

Train Model

Owner

Kingdrone

Github for the conference paper GLOD-Gaussian Likelihood OOD detector

Open source repository for the code accompanying the paper 'PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations'.

Code for "Multi-View Multi-Person 3D Pose Estimation with Plane Sweep Stereo"

Cooperative Driving Dataset: a dataset for multi-agent driving scenarios

How the Deep Q-learning method works and discuss the new ideas that makes the algorithm work

Code for Boundary-Aware Segmentation Network for Mobile and Web Applications

Deep Markov Factor Analysis (NeurIPS2021)

This is an implementation of PIFuhd based on Pytorch

Repository containing the PhD Thesis "Formal Verification of Deep Reinforcement Learning Agents"

Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

Machine Learning in Asset Management (by @firmai)

Dynamic Bottleneck for Robust Self-Supervised Exploration

A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM's

Code of our paper "Contrastive Object-level Pre-training with Spatial Noise Curriculum Learning"

Unity Propagation in Bayesian Networks Handling Inconsistency via Unity Smoothing

Run Keras models in the browser, with GPU support using WebGL

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

Detector for Log4Shell exploitation attempts

It's a powerful version of linebot

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN)

by Ailong Ma, Junjue Wang, Yanfei Zhong and Zhuo Zheng