code for paper"A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"

Related tags

Deep LearningUAGAN
Overview

PyTorch implementation of UAGAN(U-net Attention Generative Adversarial Networks)

This repository contains the source code for the paper "A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"

Author email: [email protected]

Github Github

Datasets

We use the renderings of ShapeNet and Carvana in our experiments,which are available below:

Model Structure

Prerequisites

Clone the Code Repository

git clone https://github.com/clfs0003/UAGAN

Install Python Denpendencies

cd UAGAN
pip install -r UAGAN_requirements.txt

Update Settings in config.py

You need to update hyperparametersthe of the model and path of the datasets :

    parser.add_argument('--image_dir', type=str, default='./dataset/img', help='input RGB image path')
    parser.add_argument('--mask_dir', type=str, default='./dataset/mask', help='input mask path')
    parser.add_argument('--lr', type=float, default='0.0002', help='learning rate')
    parser.add_argument('--batch_size', type=int, default='5', help='batch_size in training')
    parser.add_argument('--b1', type=float, default=0.5, help='adam: decay of first order momentum of gradient')
    parser.add_argument("--b2", type=float, default=0.999, help="adam: decay of first order momentum of gradient")
    parser.add_argument("--epoch", type=int, default=600, help="epoch in training")

Part of the experimental results are as follows

results of ShapeNet: results of ShapeNet results of Carvana: results of Carvana

Get Started

To train UAGAN, you can simply use the following command:

python3 main.py

Note: Since our paper has not been published yet, we only show the model structure and training code. When the paper is published, we will publish the full work of the paper. Welcome scholars to discuss and exchange.

License

This project is open sourced under MIT license.

Owner
Tong
Perseverance.
Tong
Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)

Diffusion Probabilistic Models for 3D Point Cloud Generation [Paper] [Code] The official code repository for our CVPR 2021 paper "Diffusion Probabilis

Shitong Luo 323 Jan 05, 2023
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is

Robotic AI & Learning Lab Berkeley 997 Dec 30, 2022
*ObjDetApp* deploys a pytorch model for object detection

*ObjDetApp* deploys a pytorch model for object detection

Will Chao 1 Dec 26, 2021
CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021

CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/

Xavier Bresson 165 Oct 25, 2022
Official PyTorch Implementation of SSMix (Findings of ACL 2021)

SSMix: Saliency-based Span Mixup for Text Classification (Findings of ACL 2021) Official PyTorch Implementation of SSMix | Paper Abstract Data augment

Clova AI Research 52 Dec 27, 2022
PyTorch implementation of probabilistic deep forecast applied to air quality.

Probabilistic Deep Forecast PyTorch implementation of a paper, titled: Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting

Abdulmajid Murad 13 Nov 16, 2022
The implementation of CVPR2021 paper Temporal Query Networks for Fine-grained Video Understanding, by Chuhan Zhang, Ankush Gupta and Andrew Zisserman.

Temporal Query Networks for Fine-grained Video Understanding 📋 This repository contains the implementation of CVPR2021 paper Temporal_Query_Networks

55 Dec 21, 2022
The code for the CVPR 2021 paper Neural Deformation Graphs, a novel approach for globally-consistent deformation tracking and 3D reconstruction of non-rigid objects.

Neural Deformation Graphs Project Page | Paper | Video Neural Deformation Graphs for Globally-consistent Non-rigid Reconstruction Aljaž Božič, Pablo P

Aljaz Bozic 134 Dec 16, 2022
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion

A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion This repo intends to release code for our work: Zhaoyang Lyu*, Zhifeng

Zhaoyang Lyu 68 Jan 03, 2023
Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel order of RGB and BGR. Simple Channel Converter for ONNX.

scc4onnx Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel

Katsuya Hyodo 16 Dec 22, 2022
Conditional Gradients For The Approximately Vanishing Ideal

Conditional Gradients For The Approximately Vanishing Ideal Code for the paper: Wirth, E., and Pokutta, S. (2022). Conditional Gradients for the Appro

IOL Lab @ ZIB 0 May 25, 2022
MG-GCN: Scalable Multi-GPU GCN Training Framework

MG-GCN MG-GCN: multi-GPU GCN training framework. For more information, please read our paper. After cloning our repository, run git submodule update -

Translational Data Analytics (TDA) Lab @GaTech 6 Oct 24, 2022
Official implementation of Protected Attribute Suppression System, ICCV 2021

Official implementation of Protected Attribute Suppression System, ICCV 2021

Prithviraj Dhar 6 Jan 01, 2023
Code for ICCV 2021 paper Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes using Scene Graphs

Graph-to-3D This is the official implementation of the paper Graph-to-3d: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs | arx

Helisa Dhamo 33 Jan 06, 2023
Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering

Yaoming Cai 5 Jul 18, 2022
Data reduction pipeline for KOALA on the AAT.

KOALA KOALA, the Kilofibre Optical AAT Lenslet Array, is a wide-field, high efficiency, integral field unit used by the AAOmega spectrograph on the 3.

4 Sep 26, 2022
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )

Differential Privacy (DP) Based Federated Learning (FL) Everything about DP-based FL you need is here. (所有你需要的DP-based FL的信息都在这里) Code Tip: the code o

wenzhu 83 Dec 24, 2022
A modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (prediction model)

ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p

Bozitao Zhong 77 Dec 22, 2022
一个目标检测的通用框架(不需要cuda编译),支持Yolo全系列(v2~v5)、EfficientDet、RetinaNet、Cascade-RCNN等SOTA网络。

一个目标检测的通用框架(不需要cuda编译),支持Yolo全系列(v2~v5)、EfficientDet、RetinaNet、Cascade-RCNN等SOTA网络。

Haoyu Xu 203 Jan 03, 2023
Unofficial PyTorch implementation of Google AI's VoiceFilter system

VoiceFilter Note from Seung-won (2020.10.25) Hi everyone! It's Seung-won from MINDs Lab, Inc. It's been a long time since I've released this open-sour

MINDs Lab 883 Jan 07, 2023