Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Last update: Sep 12, 2022

Related tags

Deep Learning NRD_decoder

Overview

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Requirements

This repository needs mmsegmentation

Training

To train the model(s) in the paper, run this command:

python tools/train.py ./configs/NRD/ade20k/NRD_r101_512x512_164k_ade20k.py

The batch size is 16 in this work. Please change the 'samples_per_gpu' in configs/base/datasets/.. accordingly

Evaluation

To evaluate my model at single-scale inference, run:

python tools/eval.py ./configs/NRD/ade20k/NRD_r101_512x512_164k_ade20k.py  {path-to-checkpoint-file}   --eval mIoU

Pre-trained Models

Results

Our model achieves the following performance on :

[Semantic segmentation results]

Model name	datasets	mIoU	mIoU (ms)
NRD-r101	ade20k (val)	44.01	45.62
NRD-x101	ade20k (val)	44.34	46.35
NRD-r101	pascal-context(val)	52.31 (59 classes)	54.1 (59 classes)
NRD-r101	pascal-context(val)	47.5 (60 classes)	40.9 (60 classes)
NRD-r50	Cityscapes (val)	79.8	80.8
NRD-r101	Cityscapes (val)	80.7	82.0

Contributing

The code is mostly taken from mmsegmentation mmsegmentation is released under the Apache 2.0 license.

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Related tags

Overview

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Requirements

Training

Evaluation

Pre-trained Models

Results

[Semantic segmentation results]

Contributing

Owner

Adelaide Intelligent Machines (AIM) Group

[CVPR'22] COAP: Learning Compositional Occupancy of People

Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

验证码识别深度学习 tensorflow 神经网络

JORLDY an open-source Reinforcement Learning (RL) framework provided by KakaoEnterprise

GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework via Self-Supervised Multi-Task Learning. Code will be available soon.

Heterogeneous Temporal Graph Neural Network

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

High-Resolution 3D Human Digitization from A Single Image.

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types

This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

optimization routines for hyperparameter tuning

Yolov5 deepsort inference，使用YOLOv5+Deepsort实现车辆行人追踪和计数，代码封装成一个Detector类，更容易嵌入到自己的项目中

TreeSubstitutionCipher - Encryption system based on trees and substitution

Unofficial PyTorch code for BasicVSR

Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.

PyTorch implementation of InstaGAN: Instance-aware Image-to-Image Translation

The repo contains the code of the ACL2020 paper `Dice Loss for Data-imbalanced NLP Tasks`

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Related tags

Overview

Dynamic Neural Representational Decoders for High-Resolution Semantic Segmentation

Requirements

Training

Evaluation

Pre-trained Models

Results

[Semantic segmentation results]

Contributing

Owner

Adelaide Intelligent Machines (AIM) Group

[CVPR'22] COAP: Learning Compositional Occupancy of People

Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

验证码识别 深度学习 tensorflow 神经网络

JORLDY an open-source Reinforcement Learning (RL) framework provided by KakaoEnterprise

GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition

Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework via Self-Supervised Multi-Task Learning. Code will be available soon.

Heterogeneous Temporal Graph Neural Network

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

High-Resolution 3D Human Digitization from A Single Image.

We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types

This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.

optimization routines for hyperparameter tuning

Yolov5 deepsort inference，使用YOLOv5+Deepsort实现车辆行人追踪和计数，代码封装成一个Detector类，更容易嵌入到自己的项目中

TreeSubstitutionCipher - Encryption system based on trees and substitution

Unofficial PyTorch code for BasicVSR

Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.

PyTorch implementation of InstaGAN: Instance-aware Image-to-Image Translation

The repo contains the code of the ACL2020 paper `Dice Loss for Data-imbalanced NLP Tasks`

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

验证码识别深度学习 tensorflow 神经网络