A MatConvNet-based implementation of the Fully-Convolutional Networks for image segmentation

Overview

MatConvNet implementation of the FCN models for semantic segmentation

This package contains an implementation of the FCN models (training and evaluation) using the MatConvNet library.

For training, look at the fcnTrain.m script, and for evaluation at fcnTest.m. The script fcnTestModelZoo.m is designed to test third party networks imported in MatConvNet (mainly from Caffe).

While we are still tuning parameters, on the PASCAL VOC 2011 validation data subset used in the FCN paper, this code has been used to train networks with this performance:

Model Test data Mean IOU Mean pix. accuracy Pixel accuracy
FCN-32s (ours) RV-VOC11 60.80 89.61 75.49
FCN-16s (ours) RV-VOC11 62.25 90.08 77.81
FCN-8s (ours) RV-VOC11 in prog. in prog. in prog.
FNC-32s (orig.) RV-VOC11 59.43 89.12 73.28
FNC-16s (orig.) RV-VOC11 62.35 90.02 75.74
FNC-8s (orig.) RV-VOC11 62.69 90.33 75.86

The original FCN models can be downloaded from the MatConvNet model repository.

About

This code was developed by

  • Sebastien Ehrhardt
  • Andrea Vedaldi

References

'Fully Convolutional Models for Semantic Segmentation', Jonathan Long, Evan Shelhamer and Trevor Darrell, CVPR, 2015 (paper).

Changes

  • v0.9.1 -- Bugfixes.
  • v0.9 -- Initial release. FCN32s and FCN16s work well.
Owner
VLFeat.org
VLFeat.org
A GPU-optional modular synthesizer in pytorch, 16200x faster than realtime, for audio ML researchers.

torchsynth The fastest synth in the universe. Introduction torchsynth is based upon traditional modular synthesis written in pytorch. It is GPU-option

torchsynth 229 Jan 02, 2023
Code for the paper "Asymptotics of ℓ2 Regularized Network Embeddings"

README Code for the paper Asymptotics of L2 Regularized Network Embeddings. Requirements Requires Stellargraph 1.2.1, Tensorflow 2.6.0, scikit-learm 0

Andrew Davison 0 Jan 06, 2022
RuDOLPH: One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP

[Paper] [Хабр] [Model Card] [Colab] [Kaggle] RuDOLPH 🦌 🎄 ☃️ One Hyper-Modal Transformer can be creative as DALL-E and smart as CLIP Russian Diffusio

AI Forever 232 Jan 04, 2023
Low-code/No-code approach for deep learning inference on devices

EzEdgeAI A concept project that uses a low-code/no-code approach to implement deep learning inference on devices. It provides a componentized framewor

On-Device AI Co., Ltd. 7 Apr 05, 2022
Code for our paper A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization,

FSRA This repository contains the dataset link and the code for our paper A Transformer-Based Feature Segmentation and Region Alignment Method For UAV

Dmmm 32 Dec 18, 2022
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

ColossalAI An integrated large-scale model training system with efficient parallelization techniques. arXiv: Colossal-AI: A Unified Deep Learning Syst

HPC-AI Tech 7.9k Jan 08, 2023
Code for paper entitled "Improving Novelty Detection using the Reconstructions of Nearest Neighbours"

NLN: Nearest-Latent-Neighbours A repository containing the implementation of the paper entitled Improving Novelty Detection using the Reconstructions

Michael (Misha) Mesarcik 4 Dec 14, 2022
Pytorch implementation of ProjectedGAN

ProjectedGAN-pytorch Pytorch implementation of ProjectedGAN (https://arxiv.org/abs/2111.01007) Note: this repository is still under developement. @InP

Dominic Rampas 17 Dec 14, 2022
A Deep Learning Framework for Neural Derivative Hedging

NNHedge NNHedge is a PyTorch based framework for Neural Derivative Hedging. The following repository was implemented to ease the experiments of our pa

GUIJIN SON 17 Nov 14, 2022
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet, ICCV 2021 Update: 2021/03/11: update our new results. Now our T2T-ViT-14 w

YITUTech 1k Dec 31, 2022
AlphaNet Improved Training of Supernet with Alpha-Divergence

AlphaNet: Improved Training of Supernet with Alpha-Divergence This repository contains our PyTorch training code, evaluation code and pretrained model

Facebook Research 87 Oct 10, 2022
Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction Requirements The code has been tested running under Python 3.7.4, with the foll

zshicode 84 Jan 01, 2023
Code for KHGT model, AAAI2021

KHGT Code for KHGT accepted by AAAI2021 Please unzip the data files in Datasets/ first. To run KHGT on Yelp data, use python labcode_yelp.py For Movi

32 Nov 29, 2022
LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

MORAI 62 Dec 17, 2022
Axel - 3D printed robotic hands and they controll with Raspberry Pi and Arduino combo

Axel It's our graduation project about 3D printed robotic hands and they control

0 Feb 14, 2022
Semantic Scholar's Author Disambiguation Algorithm & Evaluation Suite

S2AND This repository provides access to the S2AND dataset and S2AND reference model described in the paper S2AND: A Benchmark and Evaluation System f

AI2 54 Nov 28, 2022
ICON: Implicit Clothed humans Obtained from Normals

ICON: Implicit Clothed humans Obtained from Normals arXiv, December 2021. Yuliang Xiu · Jinlong Yang · Dimitrios Tzionas · Michael J. Black Table of C

Yuliang Xiu 1.1k Dec 30, 2022
How to Learn a Domain Adaptive Event Simulator? ACM MM, 2021

LETGAN How to Learn a Domain Adaptive Event Simulator? ACM MM 2021 Running Environment: pytorch=1.4, 1 NVIDIA-1080TI. More details can be found in pap

CVTEAM 4 Sep 20, 2022
🛠 All-in-one web-based IDE specialized for machine learning and data science.

All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu

Machine Learning Tooling 2.9k Jan 09, 2023
Code for Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021)

Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021) Single-cause Perturbation (SCP) is a framework to estimate the m

Zhaozhi Qian 9 Sep 28, 2022