Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)

Overview

Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)

Introduction

Official implementation of Dynamic Multi-scale Filters for Semantic Segmentation (Paper).
🔥 🔥 DMNet is on MMsegmentation. 🔥 🔥

@InProceedings{He_2019_ICCV,
author = {He, Junjun and Deng, Zhongying and Qiao, Yu},
title = {Dynamic Multi-Scale Filters for Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}

Overview

Framework

image

Results and models

Cityscapes

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
DMNet R-50-D8 512x1024 40000 7.0 3.66 77.78 79.14 config model | log
DMNet R-101-D8 512x1024 40000 10.6 2.54 78.37 79.72 config model | log
DMNet R-50-D8 769x769 40000 7.9 1.57 78.49 80.27 config model | log
DMNet R-101-D8 769x769 40000 12.0 1.01 77.62 78.94 config model | log
DMNet R-50-D8 512x1024 80000 - - 79.07 80.22 config model | log
DMNet R-101-D8 512x1024 80000 - - 79.64 80.67 config model | log
DMNet R-50-D8 769x769 80000 - - 79.22 80.55 config model | log
DMNet R-101-D8 769x769 80000 - - 79.19 80.65 config model | log

ADE20K

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
DMNet R-50-D8 512x512 80000 9.4 20.95 42.37 43.62 config model | log
DMNet R-101-D8 512x512 80000 13.0 13.88 45.34 46.13 config model | log
DMNet R-50-D8 512x512 160000 - - 43.15 44.17 config model | log
DMNet R-101-D8 512x512 160000 - - 45.42 46.76 config model | log
Lipschitz-constrained Unsupervised Skill Discovery

Lipschitz-constrained Unsupervised Skill Discovery This repository is the official implementation of Seohong Park, Jongwook Choi*, Jaekyeom Kim*, Hong

Seohong Park 17 Dec 18, 2022
Code Repository for The Kaggle Book, Published by Packt Publishing

The Kaggle Book Data analysis and machine learning for competitive data science Code Repository for The Kaggle Book, Published by Packt Publishing "Lu

Packt 1.6k Jan 07, 2023
“Robust Lightweight Facial Expression Recognition Network with Label Distribution Training”, AAAI 2021.

EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI

Zengqun Zhao 119 Jan 08, 2023
Huawei Hackathon 2021 - Sweden (Stockholm)

huawei-hackathon-2021 Contributors DrakeAxelrod Challenge Requirements: python=3.8.10 Standard libraries (no importing) Important factors: Data depend

Drake Axelrod 32 Nov 08, 2022
Person Re-identification

Person Re-identification Final project of Computer Vision Table of content Person Re-identification Table of content Students: Proposed method Dataset

Nguyễn Hoàng Quân 4 Jun 17, 2021
Final project for machine learning (CSC 590). Detection of hepatitis C and progression through blood samples.

Hepatitis C Blood Based Detection Final project for machine learning (CSC 590). Dataset from Kaggle. Using data from previous hepatitis C blood panels

Jennefer Maldonado 1 Dec 28, 2021
Original code for "Zero-Shot Domain Adaptation with a Physics Prior"

Zero-Shot Domain Adaptation with a Physics Prior [arXiv] [sup. material] - ICCV 2021 Oral paper, by Attila Lengyel, Sourav Garg, Michael Milford and J

Attila Lengyel 40 Dec 21, 2022
Pull sensitive data from users on windows including discord tokens and chrome data.

⭐ For a 🍪 Pegasus Pull sensitive data from users on windows including discord tokens and chrome data. Features 🟩 Discord tokens 🟩 Geolocation data

Addi 44 Dec 31, 2022
[ ICCV 2021 Oral ] Our method can estimate camera poses and neural radiance fields jointly when the cameras are initialized at random poses in complex scenarios (outside-in scenes, even with less texture or intense noise )

GNeRF This repository contains official code for the ICCV 2021 paper: GNeRF: GAN-based Neural Radiance Field without Posed Camera. This implementation

Quan Meng 191 Dec 26, 2022
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization

CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090

THUDM 28 Dec 09, 2022
Code and Data for the paper: Molecular Contrastive Learning with Chemical Element Knowledge Graph [AAAI 2022]

Knowledge-enhanced Contrastive Learning (KCL) Molecular Contrastive Learning with Chemical Element Knowledge Graph [ AAAI 2022 ]. We construct a Chemi

Fangyin 58 Dec 26, 2022
Official implementation of the Neurips 2021 paper Searching Parameterized AP Loss for Object Detection.

Parameterized AP Loss By Chenxin Tao, Zizhang Li, Xizhou Zhu, Gao Huang, Yong Liu, Jifeng Dai This is the official implementation of the Neurips 2021

46 Jul 06, 2022
Attendance Monitoring with Face Recognition using Python

Attendance Monitoring with Face Recognition using Python A python GUI integrated attendance system using face recognition to take attendance. In this

Vaibhav Rajput 2 Jun 21, 2022
DECAF: Deep Extreme Classification with Label Features

DECAF DECAF: Deep Extreme Classification with Label Features @InProceedings{Mittal21, author = "Mittal, A. and Dahiya, K. and Agrawal, S. and Sain

46 Nov 06, 2022
HNN: Human (Hollywood) Neural Network

HNN: Human (Hollywood) Neural Network Learn the top 1000 actors on IMDB with your very own low cost, highly parallel, CUDAless biological neural netwo

Madhava Jay 0 Dec 21, 2021
Pseudo-mask Matters in Weakly-supervised Semantic Segmentation

Pseudo-mask Matters in Weakly-supervised Semantic Segmentation By Yi Li, Zhanghui Kuang, Liyang Liu, Yimin Chen, Wayne Zhang SenseTime, Tsinghua Unive

33 Oct 14, 2022
Numba-accelerated Pythonic implementation of MPDATA with examples in Python, Julia and Matlab

PyMPDATA PyMPDATA is a high-performance Numba-accelerated Pythonic implementation of the MPDATA algorithm of Smolarkiewicz et al. used in geophysical

Atmospheric Cloud Simulation Group @ Jagiellonian University 15 Nov 23, 2022
Cache Requests in Deta Bases and Echo them with Deta Micros

Deta Echo Cache Leverage the awesome Deta Micros and Deta Base to cache requests and echo them as needed. Stop worrying about slow public APIs or agre

Gingerbreadfork 8 Dec 07, 2021
GPOEO is a micro-intrusive GPU online energy optimization framework for iterative applications

GPOEO GPOEO is a micro-intrusive GPU online energy optimization framework for iterative applications. We also implement ODPP [1] as a comparison. [1]

瑞雪轻飏 8 Sep 10, 2022
Extreme Rotation Estimation using Dense Correlation Volumes

Extreme Rotation Estimation using Dense Correlation Volumes This repository contains a PyTorch implementation of the paper: Extreme Rotation Estimatio

Ruojin Cai 29 Nov 18, 2022