[ICCV 2021 Oral] Mining Latent Classes for Few-shot Segmentation

Overview

Mining Latent Classes for Few-shot Segmentation

Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao.

This codebase contains baseline of our paper Mining Latent Classes for Few-shot Segmentation, ICCV 2021 Oral.

Several key modifications to the simple yet effective metric learning framework:

  • Remove the final residual stage in ResNet for stronger generalization
  • Remove the final ReLU for feature matching
  • Freeze all the BatchNorms from ImageNet pretrained model

Environment

This codebase was tested with the following environment configurations.

  • Ubuntu 18.04
  • CUDA 11.2
  • Python 3.7.4
  • PyTorch 1.6.0
  • Pillow, numpy, torchvision, tqdm
  • Two NVIDIA V100 GPUs

Getting Started

Data Preparation

Pretrained model: ResNet-50 | ResNet-101

Dataset: Pascal JPEGImages | SegmentationClass | ImageSets

File Organization

├── ./pretrained
    ├── resnet50.pth
    └── resnet101.pth
    
├── [Your Pascal Path]
    ├── JPEGImages
    │   ├── 2007_000032.jpg
    │   └── ...
    │
    ├── SegmentationClass
    │   ├── 2007_000032.png
    │   └── ...
    │
    └── ImageSets
        ├── train.txt
        └── val.txt

Run the Code

CUDA_VISIBLE_DEVICES=0,1 python -W ignore main.py \
  --dataset pascal --data-root [Your Pascal Path] \
  --backbone resnet50 --fold 0 --shot 1

You may change the backbone from resnet50 to resnet101, change the fold from 0 to 1/2/3, or change the shot from 1 to 5 for other settings.

Performance and Trained Models

Here we report the performance of our modified baseline on Pascal. You can click on the numbers to download corresponding trained models.

The training time is measured on two V100 GPUs. Compared with other works, our method is efficient to train.

Setting Backbone Training time / fold Fold 0 Fold 1 Fold 2 Fold 3 Mean
1-shot ResNet-50 40 minutes 54.9 66.5 61.7 48.3 57.9
1-shot ResNet-101 1.1 hours 57.2 68.5 61.3 53.3 60.1
5-shot ResNet-50 2.3 hours 61.6 70.3 70.5 56.4 64.7
5-shot ResNet-101 3.5 hours 64.2 74.0 71.5 61.3 67.8

Acknowledgement

We thank PANet, PPNet, PFENet and other FSS works for their great contributions.

Citation

If you find this project useful for your research, please consider citing:

@inproceedings{yang2021mining,
  title={Mining Latent Classes for Few-shot Segmentation},
  author={Yang, Lihe and Zhuo, Wei and Qi, Lei and Shi, Yinghuan and Gao, Yang},
  booktitle={ICCV},
  year={2021}
}
Owner
Lihe Yang
Master student at Nanjing University, Computer Vision
Lihe Yang
Wider-Yolo Kütüphanesi ile Yüz Tespit Uygulamanı Yap

WIDER-YOLO : Yüz Tespit Uygulaması Yap Wider-Yolo Kütüphanesinin Kullanımı 1. Wider Face Veri Setini İndir Train Dataset Val Dataset Test Dataset Not:

Kadir Nar 6 Aug 22, 2022
Reproducing Results from A Hybrid Approach to Targeting Social Assistance

title author date output Reproducing Results from A Hybrid Approach to Targeting Social Assistance Lendie Follett and Heath Henderson 12/28/2021 html_

Lendie Follett 0 Jan 06, 2022
A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis

WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install

Yuchao Zhang 204 Jul 14, 2022
MacroTools provides a library of tools for working with Julia code and expressions.

MacroTools.jl MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system an

FluxML 278 Dec 11, 2022
SmallInitEmb - LayerNorm(SmallInit(Embedding)) in a Transformer to improve convergence

SmallInitEmb LayerNorm(SmallInit(Embedding)) in a Transformer I find that when t

PENG Bo 11 Dec 25, 2022
An unofficial styleguide and best practices summary for PyTorch

A PyTorch Tools, best practices & Styleguide This is not an official style guide for PyTorch. This document summarizes best practices from more than a

IgorSusmelj 1.5k Jan 05, 2023
This repository attempts to replicate the SqueezeNet architecture and implement the same on an image classification task.

SqueezeNet-Implementation This repository attempts to replicate the SqueezeNet architecture using TensorFlow discussed in the research paper: "Squeeze

Rohan Mathur 3 Dec 13, 2022
fklearn: Functional Machine Learning

fklearn: Functional Machine Learning fklearn uses functional programming principles to make it easier to solve real problems with Machine Learning. Th

nubank 1.4k Dec 07, 2022
[ICCV2021] Official Pytorch implementation for SDGZSL (Semantics Disentangling for Generalized Zero-Shot Learning)

Semantics Disentangling for Generalized Zero-shot Learning This is the official implementation for paper Zhi Chen, Yadan Luo, Ruihong Qiu, Zi Huang, J

25 Dec 06, 2022
Personal project about genus-0 meshes, spherical harmonics and a cow

How to transform a cow into spherical harmonics ? Spot the cow, from Keenan Crane's blog Context In the field of Deep Learning, training on images or

3 Aug 22, 2022
Easy-to-use library to boost AI inference leveraging state-of-the-art optimization techniques.

NEW RELEASE How Nebullvm Works • Tutorials • Benchmarks • Installation • Get Started • Optimization Examples Discord | Website | LinkedIn | Twitter Ne

Nebuly 1.7k Dec 31, 2022
GRF: Learning a General Radiance Field for 3D Representation and Rendering

GRF: Learning a General Radiance Field for 3D Representation and Rendering [Paper] [Video] GRF: Learning a General Radiance Field for 3D Representatio

Alex Trevithick 243 Dec 29, 2022
alfred-py: A deep learning utility library for **human**

Alfred Alfred is command line tool for deep-learning usage. if you want split an video into image frames or combine frames into a single video, then a

JinTian 800 Jan 03, 2023
TextureGAN in Pytorch

TextureGAN This code is our PyTorch implementation of TextureGAN [Project] [Arxiv] TextureGAN is a generative adversarial network conditioned on sketc

Patsorn 147 Dec 14, 2022
Code for the paper "Multi-task problems are not multi-objective"

Multi-Task problems are not multi-objective This is the code for the paper "Multi-Task problems are not multi-objective" in which we show that the com

Michael Ruchte 5 Aug 19, 2022
KaziText is a tool for modelling common human errors.

KaziText KaziText is a tool for modelling common human errors. It estimates probabilities of individual error types (so called aspects) from grammatic

ÚFAL 3 Nov 24, 2022
Source code for "Interactive All-Hex Meshing via Cuboid Decomposition [SIGGRAPH Asia 2021]".

Interactive All-Hex Meshing via Cuboid Decomposition Video demonstration This repository contains an interactive software to the PolyCube-based hex-me

Lingxiao Li 131 Dec 05, 2022
Official Implementation of "Third Time's the Charm? Image and Video Editing with StyleGAN3" https://arxiv.org/abs/2201.13433

Third Time's the Charm? Image and Video Editing with StyleGAN3 Yuval Alaluf*, Or Patashnik*, Zongze Wu, Asif Zamir, Eli Shechtman, Dani Lischinski, Da

531 Dec 20, 2022
Simple implementation of Mobile-Former on Pytorch

Simple-implementation-of-Mobile-Former At present, only the model but no trained. There may be some bug in the code, and some details may be different

Acheung 103 Dec 31, 2022
CVPR 2021 Challenge on Super-Resolution Space

Learning the Super-Resolution Space Challenge NTIRE 2021 at CVPR Learning the Super-Resolution Space challenge is held as a part of the 6th edition of

andreas 104 Oct 26, 2022