[cvpr22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

Overview

PS-MT

[cvpr22] Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation

by Yuyuan Liu, Yu Tian, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis and Gustavo Carneiro

Computer Vision and Pattern Recognition Conference (CVPR), 2022

image

Installation

Please install the dependencies and dataset based on this installation document.

Getting start

Please follow this instruction document to reproduce our results.

Results

Pascal VOC12 dataset

  1. augmented set

    Backbone 1/16 (662) 1/8 (1323) 1/4 (2646) 1/2 (5291)
    50 72.83 75.70 76.43 77.88
    101 75.50 78.20 78.72 79.76
  2. high quality set (based on res101)

    1/16 (92) 1/8 (183) 1/4 (366) 1/2 (732) full (1464)
    65.80 69.58 76.57 78.42 80.01

CityScape dataset

  1. following the setting of CAC (720x720, CE supervised loss)

    Backbone slid. eval 1/8 (372) 1/4 (744) 1/2 (1488)
    50 74.37 75.15 76.02
    50 75.76 76.92 77.64
    101 76.89 77.60 79.09
  2. following the setting of CPS (800x800, OHEM supervised loss)

    Backbone slid. eval 1/8 (372) 1/4 (744) 1/2 (1488)
    50 77.12 78.38 79.22

Training details

Some examples of training details, including:

  1. VOC12 dataset in this wandb link.
  2. Cityscapes dataset in this wandb link (w/ 1-teacher inference).

In details, after clicking the run, you can checkout:

  1. overall information (e.g., training command line, hardware information and training time).
  2. training details (e.g., loss curves, validation results and visualization)
  3. output logs (well, sometimes might crash ...)

Acknowledgement & Citation

The code is highly based on the CCT. Many thanks for their great work.

Please consider citing this project in your publications if it helps your research.

@article{liu2021perturbed,
  title={Perturbed and Strict Mean Teachers for Semi-supervised Semantic Segmentation},
  author={Liu, Yuyuan and Tian, Yu and Chen, Yuanhong and Liu, Fengbei and Belagiannis, Vasileios and Carneiro, Gustavo},
  journal={arXiv preprint arXiv:2111.12903},
  year={2021}
}

TODO

  • Code of deeplabv3+ for voc12
  • Code of deeplabv3+ for cityscapes
  • Code of pspnet for voc12
Owner
Yuyuan Liu
Yuyuan Liu
CS50x-AI - Artificial Intelligence with Python from Harvard University

CS50x-AI Artificial Intelligence with Python from Harvard University 📖 Table of

Hosein Damavandi 6 Aug 22, 2022
Diffusion Normalizing Flow (DiffFlow) Neurips2021

Diffusion Normalizing Flow (DiffFlow) Reproduce setup environment The repo heavily depends on jam, a personal toolbox developed by Qsh.zh. The API may

76 Jan 01, 2023
Atif Hassan 103 Dec 14, 2022
BERT model training impelmentation using 1024 A100 GPUs for MLPerf Training v1.1

Pre-trained checkpoint and bert config json file Location of checkpoint and bert config json file This MLCommons members Google Drive location contain

SAIT (Samsung Advanced Institute of Technology) 12 Apr 27, 2022
Biomarker identification for COVID-19 Severity in BALF cells Single-cell RNA-seq data

scBALF Covid-19 dataset Analysis Here is the Github page that has the codes for the bioinformatics pipeline described in the paper COVID-Datathon: Bio

Nami Niyakan 2 May 21, 2022
Learning Open-World Object Proposals without Learning to Classify

Learning Open-World Object Proposals without Learning to Classify Pytorch implementation for "Learning Open-World Object Proposals without Learning to

Dahun Kim 149 Dec 22, 2022
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!

Peter Lin 6.5k Jan 04, 2023
A flexible framework of neural networks for deep learning

Chainer: A deep learning framework Website | Docs | Install Guide | Tutorials (ja) | Examples (Official, External) | Concepts | ChainerX Forum (en, ja

Chainer 5.8k Jan 06, 2023
Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity

Cross-lingual Transfer for Speech Processing using Acoustic Language Similarity Indic TTS Samples can be found at https://peter-yh-wu.github.io/cross-

Peter Wu 1 Nov 12, 2022
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"

Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr

43 Nov 21, 2022
[CVPR2022] Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos

Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos Created by Muheng Li, Lei Chen, Yueqi Duan, Zhilan Hu, Jianjiang Feng, Jie

58 Dec 23, 2022
Framework for evaluating ANNS algorithms on billion scale datasets.

Billion-Scale ANN http://big-ann-benchmarks.com/ Install The only prerequisite is Python (tested with 3.6) and Docker. Works with newer versions of Py

Harsha Vardhan Simhadri 132 Dec 24, 2022
Controlling the MicriSpotAI robot from scratch

Abstract: The SpotMicroAI project is designed to be a low cost, easily built quadruped robot. The design is roughly based off of Boston Dynamics quadr

Florian Wilk 405 Jan 05, 2023
Bridging Vision and Language Model

BriVL BriVL (Bridging Vision and Language Model) 是首个中文通用图文多模态大规模预训练模型。BriVL模型在图文检索任务上有着优异的效果,超过了同期其他常见的多模态预训练模型(例如UNITER、CLIP)。 BriVL论文:WenLan: Bridgi

235 Dec 27, 2022
Unet network with mean teacher for altrasound image segmentation

Unet network with mean teacher for altrasound image segmentation

5 Nov 21, 2022
SpanNER: Named EntityRe-/Recognition as Span Prediction

SpanNER: Named EntityRe-/Recognition as Span Prediction Overview | Demo | Installation | Preprocessing | Prepare Models | Running | System Combination

NeuLab 104 Dec 17, 2022
Mesh Graphormer is a new transformer-based method for human pose and mesh reconsruction from an input image

MeshGraphormer ✨ ✨ This is our research code of Mesh Graphormer. Mesh Graphormer is a new transformer-based method for human pose and mesh reconsructi

Microsoft 251 Jan 08, 2023
Statsmodels: statistical modeling and econometrics in Python

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

statsmodels 8.1k Jan 02, 2023
PyTorch code for our paper "Attention in Attention Network for Image Super-Resolution"

Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten

Haoyu Chen 71 Dec 30, 2022
This is a repo of basic Machine Learning!

Basic Machine Learning This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resource

Ekram Asif 53 Dec 31, 2022