[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
Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)

To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/

32 Dec 26, 2022
Extracts essential Mediapipe face landmarks and arranges them in a sequenced order.

simplified_mediapipe_face_landmarks Extracts essential Mediapipe face landmarks and arranges them in a sequenced order. The default 478 Mediapipe face

Irfan 13 Oct 04, 2022
The Simplest DCGAN Implementation

DCGAN in TensorLayer This is the TensorLayer implementation of Deep Convolutional Generative Adversarial Networks. Looking for Text to Image Synthesis

TensorLayer Community 310 Dec 13, 2022
Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight

Revisiting RCAN: Improved Training for Image Super-Resolution Introduction Image super-resolution (SR) is a fast-moving field with novel architectures

Zudi Lin 76 Dec 01, 2022
HyDiff: Hybrid Differential Software Analysis

HyDiff: Hybrid Differential Software Analysis This repository provides the tool and the evaluation subjects for the paper HyDiff: Hybrid Differential

Yannic Noller 22 Oct 20, 2022
Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)

Swin-Transformer-Tensorflow A direct translation of the official PyTorch implementation of "Swin Transformer: Hierarchical Vision Transformer using Sh

52 Dec 29, 2022
Code repository for the paper "Tracking People with 3D Representations"

Tracking People with 3D Representations Code repository for the paper "Tracking People with 3D Representations" (paper link) (project site). Jathushan

Jathushan Rajasegaran 77 Dec 03, 2022
Spatio-Temporal Entropy Model (STEM) for end-to-end leaned video compression.

Spatio-Temporal Entropy Model A Pytorch Reproduction of Spatio-Temporal Entropy Model (STEM) for end-to-end leaned video compression. More details can

16 Nov 28, 2022
[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l

ZJU-VIPA 37 Nov 10, 2022
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation

STCN Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [a

Rex Cheng 456 Dec 12, 2022
It is a system used to detect bone fractures. using techniques deep learning and image processing

MohammedHussiengadalla-Intelligent-Classification-System-for-Bone-Fractures It is a system used to detect bone fractures. using techniques deep learni

Mohammed Hussien 7 Nov 11, 2022
Clean and readable code for Decision Transformer: Reinforcement Learning via Sequence Modeling

Minimal implementation of Decision Transformer: Reinforcement Learning via Sequence Modeling in PyTorch for mujoco control tasks in OpenAI gym

Nikhil Barhate 104 Jan 06, 2023
Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT)

Complete-IoU Loss and Cluster-NMS for Improving Object Detection and Instance Segmentation. Our paper is accepted by IEEE Transactions on Cybernetics

290 Dec 25, 2022
A configurable, tunable, and reproducible library for CTR prediction

FuxiCTR This repo is the community dev version of the official release at huawei-noah/benchmark/FuxiCTR. Click-through rate (CTR) prediction is an cri

XUEPAI 397 Dec 30, 2022
[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects YouTube | arXiv Prerequisites Kaolin is available here:

Denys Rozumnyi 107 Dec 26, 2022
Learned model to estimate number of distinct values (NDV) of a population using a small sample.

Learned NDV estimator Learned model to estimate number of distinct values (NDV) of a population using a small sample. The model approximates the maxim

2 Nov 21, 2022
Multi-task head pose estimation in-the-wild

Multi-task head pose estimation in-the-wild We provide C++ code in order to replicate the head-pose experiments in our paper https://ieeexplore.ieee.o

Roberto Valle 26 Oct 06, 2022
[CIKM 2021] Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning

Enhancing Aspect-Based Sentiment Analysis with Supervised Contrastive Learning. This repo contains the PyTorch code and implementation for the paper E

Akuchi 18 Dec 22, 2022
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.

OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters

THUNLP 386 Dec 26, 2022
ZEBRA: Zero Evidence Biometric Recognition Assessment

ZEBRA: Zero Evidence Biometric Recognition Assessment license: LGPLv3 - please reference our paper version: 2020-06-11 author: Andreas Nautsch (EURECO

Voice Privacy Challenge 2 Dec 12, 2021