"Segmenter: Transformer for Semantic Segmentation" reproduced via mmsegmentation

Last update: Feb 24, 2022

Overview

Segmenter-based-on-OpenMMLab

"Segmenter: Transformer for Semantic Segmentation, arxiv 2105.05633." reproduced via mmsegmentation.

We reproduce Segmenter via mmsegmentation based on official open-sourced code.

Environment

python=3.7
pytorch=1.7.1
torchvision=0.8.2
cudatoolkit=10.1
mmcv-full=1.3.10
mmsegmentation=0.16.0

Note: You should install pytorch with a version higher than 1.7, because the pretrained model of DeiT is saved via 1.7+ pytorch. Otherwise you may encounter some errors while loading the state_dict.

Results on ADE20K

The passwds of download links are all 'nopw'.

Exp	Name	backbone	Our mIoU-SS	mIoU in paper	Resolution	BS	Download
4th line in Table3	Seg-B†-Linear/16	DeiT-B	46.83	47.10	512x512	8	model	config	log
4th line in Table6	Seg-B†-Mask/16	DeiT-B	48.41	47.67	512x512	8	model	config	log
6th line in Table3	Seg-B -Linear/16	ViT-B	45.70	45.69	512x512	8	model	config	log

Owner

EricKani

GitHub Repository

Resco: A simple python package that report the effect of deep residual learning

resco Description resco is a simple python package that report the effect of dee

1 Jun 28, 2022

Oriented Response Networks, in CVPR 2017

Oriented Response Networks [Home] [Project] [Paper] [Supp] [Poster] Torch Implementation The torch branch contains: the official torch implementation

217 Dec 12, 2022

[ECCVW2020] Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DiMP)

Feel free to visit my homepage Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DIMP) [ECCVW2020 paper] Presentation

35 Oct 26, 2022

Pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments

Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of

300 Nov 22, 2022

Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning

Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:

1 Jan 27, 2022

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data arXiv This is the code base for weakly supervised NER. We provide a

92 Jan 04, 2023

This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation withNoisy Multi-feedback"

Curriculum_disentangled_recommendation This is the repository of the NeurIPS 2021 paper "Curriculum Disentangled Recommendation with Noisy Multi-feedb

14 Dec 20, 2022

Official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021.

Introduction This repository is the official PyTorch implementation of Data-free Knowledge Distillation for Object Detection, WACV 2021. Data-free Kno

50 Jan 05, 2023

Code and data (Incidents Dataset) for ECCV 2020 Paper "Detecting natural disasters, damage, and incidents in the wild".

Incidents Dataset See the following pages for more details: Project page: IncidentsDataset.csail.mit.edu. ECCV 2020 Paper "Detecting natural disasters

67 Dec 27, 2022

pytorchのスライス代入操作をonnxに変換する際にScatterNDならないようにするサンプル

pytorch_remove_ScatterND pytorchのスライス代入操作をonnxに変換する際にScatterNDならないようにするサンプル。スライスしたtensorにそのまま代入してしまうとScatterNDになるため、計算結果をcatで新しいtensorにする。 python ver

2 Dec 01, 2022

Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

1.8k Jan 07, 2023

Hand gesture recognition model that can be used as a remote control for a smart tv.

Gesture_recognition The training data consists of a few hundred videos categorised into one of the five classes. Each video (typically 2-3 seconds lon

1 Aug 11, 2022

This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated p

9 Jul 14, 2022