TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

Related tags

Deep LearningTransFGU
Overview

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li, Rong Jin

[Preprint]

Getting Started

Create the environment

# create conda env
conda create -n TransFGU python=3.8
# activate conda env
conda activate TransFGU
# install pytorch
conda install pytorch=1.8 torchvision cudatoolkit=10.1
# install other dependencies
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.8.0/index.html
pip install -r requirements.txt

Dataset Preparation

the structure of dataset folders should be as follow:

data/
    │── MSCOCO/
    │     ├── images/
    │     │     ├── train2017/
    │     │     └── val2017/
    │     └── annotations/
    │           ├── train2017/
    │           ├── val2017/
    │           ├── instances_train2017.json
    │           └── instances_val2017.json
    │── Cityscapes/
    │     ├── leftImg8bit/
    │     │     ├── train/
    │     │     │       ├── aachen
    │     │     │       └── ...
    │     │     └──── val/
    │     │             ├── frankfurt
    │     │             └── ...
    │     └── gtFine/
    │           ├── train/
    │           │       ├── aachen
    │           │       └── ...
    │           └──── val/
    │                   ├── frankfurt
    │                   └── ...
    │── PascalVOC/
    │     ├── JPEGImages/
    │     ├── SegmentationClass/
    │     └── ImageSets/
    │           └── Segmentation/
    │                   ├── train.txt
    │                   └── val.txt
    └── LIP/
          ├── train_images/
          ├── train_segmentations/
          ├── val_images/
          ├── val_segmentations/
          ├── train_id.txt
          └── val_id.txt

Model download

Name mIoU Pixel Accuracy Model
COCOStuff-27 16.19 44.52 Google Drive
COCOStuff-171 11.93 34.32 Google Drive
COCO-80 12.69 64.31 Google Drive
Cityscapes 16.83 77.92 Google Drive
Pascal-VOC 37.15 83.59 Google Drive
LIP-5 25.16 65.76 Google Drive
LIP-16 15.49 60.08 Google Drive
LIP-19 12.24 42.52 Google Drive

Train and Evaluate Our Method

To train and evaluate our method on different datasets under desired granularity level, please follow the instructions here.

Citation

If you find our work useful in your research, please consider citing:

@article{yin2021transfgu,
  title={TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation},
  author={Zhaoyun, Yin and Pichao, Wang and Fan, Wang and Xianzhe, Xu and Hanling, Zhang and Hao, Li and Rong, Jin},
  journal={arXiv preprint arXiv:2112.01515},
  year={2021}
}

LICENSE

The code is released under the MIT license.

Copyright

Copyright (C) 2010-2021 Alibaba Group Holding Limited.

Owner
DamoCV
CV team of DAMO academy
DamoCV
Segmentation Training Pipeline

Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed

Musket ML 52 Dec 12, 2022
[CVPR 2021] "Multimodal Motion Prediction with Stacked Transformers": official code implementation and project page.

mmTransformer Introduction This repo is official implementation for mmTransformer in pytorch. Currently, the core code of mmTransformer is implemented

DeciForce: Crossroads of Machine Perception and Autonomy 232 Dec 31, 2022
Cours d'Algorithmique Appliquée avec Python pour BTS SIO SISR

Course: Introduction to Applied Algorithms with Python (in French) This is the source code of the website for the Applied Algorithms with Python cours

Loic Yvonnet 0 Jan 27, 2022
Personals scripts using ageitgey/face_recognition

HOW TO USE pip3 install requirements.txt Add some pictures of known people in the folder 'people' : a) Create a folder called by the name of the perso

Antoine Bollengier 1 Jan 06, 2022
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
Voila - Voilà turns Jupyter notebooks into standalone web applications

Rendering of live Jupyter notebooks with interactive widgets. Introduction Voilà turns Jupyter notebooks into standalone web applications. Unlike the

Voilà Dashboards 4.5k Jan 03, 2023
Label Studio is a multi-type data labeling and annotation tool with standardized output format

Website • Docs • Twitter • Join Slack Community What is Label Studio? Label Studio is an open source data labeling tool. It lets you label data types

Heartex 11.7k Jan 09, 2023
Motion and Shape Capture from Sparse Markers

MoSh++ This repository contains the official chumpy implementation of mocap body solver used for AMASS: AMASS: Archive of Motion Capture as Surface Sh

Nima Ghorbani 135 Dec 23, 2022
NeurIPS'21 Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows

NeurIPS'21 Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows This repo contains the code for the paper Tractable Densit

Layer6 Labs 4 Dec 12, 2022
Draw like Bob Ross using the power of Neural Networks (With PyTorch)!

Draw like Bob Ross using the power of Neural Networks! (+ Pytorch) Learning Process Visualization Getting started Install dependecies Requires python3

Kendrick Tan 116 Mar 07, 2022
An addernet CUDA version

Training addernet accelerated by CUDA Usage cd adder_cuda python setup.py install cd .. python main.py Environment pytorch 1.10.0 CUDA 11.3 benchmark

LingXY 4 Jun 20, 2022
PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)

1-bit Wide ResNet PyTorch implementation of training 1-bit Wide ResNets from this paper: Training wide residual networks for deployment using a single

Sergey Zagoruyko 122 Dec 07, 2022
CRNN With PyTorch

CRNN-PyTorch Implementation of https://arxiv.org/abs/1507.05717

Vadim 4 Sep 01, 2022
Self-Supervised Contrastive Learning of Music Spectrograms

Self-Supervised Music Analysis Self-Supervised Contrastive Learning of Music Spectrograms Dataset Songs on the Billboard Year End Hot 100 were collect

27 Dec 10, 2022
Dark Finix: All in one hacking framework with almost 100 tools

Dark Finix - Hacking Framework. Dark Finix is a all in one hacking framework wit

Md. Nur habib 2 Feb 18, 2022
Context-Sensitive Misspelling Correction of Clinical Text via Conditional Independence, CHIL 2022

cim-misspelling Pytorch implementation of Context-Sensitive Spelling Correction of Clinical Text via Conditional Independence, CHIL 2022. This model (

Juyong Kim 11 Dec 19, 2022
Adjust Decision Boundary for Class Imbalanced Learning

Adjusting Decision Boundary for Class Imbalanced Learning This repository is the official PyTorch implementation of WVN-RS, introduced in Adjusting De

Peyton Byungju Kim 16 Jan 04, 2023
Multistream CNN for Robust Acoustic Modeling

Multistream Convolutional Neural Network (CNN) A multistream CNN is a novel neural network architecture for robust acoustic modeling in speech recogni

ASAPP Research 37 Sep 21, 2022
A TensorFlow implementation of Neural Program Synthesis from Diverse Demonstration Videos

ViZDoom http://vizdoom.cs.put.edu.pl ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is pri

Hyeonwoo Noh 1 Aug 19, 2020
(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int

CVMI Lab 228 Dec 25, 2022