Efficient semantic image segmentation with superpixel pooling

2018-06-07 · Mathijs Schuurmans, Maxim Berman, Matthew B. Blaschko

In this work, we evaluate the use of superpixel pooling layers in deep network architectures for semantic segmentation. Superpixel pooling is a flexible and efficient replacement for other pooling strategies that incorporates spatial prior information. We propose a simple and efficient GPU-implementation of the layer and explore several designs for the integration of the layer into existing network architectures. We provide experimental results on the IBSR and Cityscapes dataset, demonstrating that superpixel pooling can be leveraged to consistently increase network accuracy with minimal computational overhead. Source code is available at https://github.com/bermanmaxim/superpixPool

📄 PDF Abstract BibTeX arXiv:1806.02705

Code (1)

bermanmaxim/superpixPool 공식 구현 pytorch

Tasks

GPUImage Segmentation Semantic Segmentation

STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling

2016-04-08 · CVPR 2017 7 · Yang He, Wei-Chen Chiu, Margret Keuper, Mario Fritz

We propose a novel superpixel-based multi-view convolutional neural network for semantic image segmentation. The proposed network produces a high quality segmentation of a single image by leveraging information from addi…

Image Segmentation Optical Flow Estimation RGBD Semantic Segmentation Segmentation+2

Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation

2020-07-20 · ECCV 2020 8 · Cheng Ouyang, Carlo Biffi, Chen Chen, Turkay Kart 외

Few-shot semantic segmentation (FSS) has great potential for medical imaging applications. Most of the existing FSS techniques require abundant annotated semantic classes for training. However, these methods may not be a…

Cardiac Segmentation Few-Shot Semantic Segmentation Image Segmentation Medical Image Segmentation+4

SANet:Superpixel Attention Network for Skin Lesion Attributes Detection

2019-10-20 · Xinzi He, Baiying Lei, Tianfu Wang

The accurate detection of lesion attributes is meaningful for both the computeraid diagnosis system and dermatologists decisions. However, unlike lesion segmentation and melenoma classification, there are few deep learni…

Attribute General Classification Lesion Segmentation Task 2

Image Classification using Graph Neural Network and Multiscale Wavelet Superpixels

2022-01-29 · Varun Vasudevan, Maxime Bassenne, Md Tauhidul Islam, Lei Xing

Prior studies using graph neural networks (GNNs) for image classification have focused on graphs generated from a regular grid of pixels or similar-sized superpixels. In the latter, a single target number of superpixels …

Classification Graph Classification Graph Neural Network image-classification+2

Superpixel-based Refinement for Object Proposal Generation

2021-01-12 · Christian Wilms, Simone Frintrop

Precise segmentation of objects is an important problem in tasks like class-agnostic object proposal generation or instance segmentation. Deep learning-based systems usually generate segmentations of objects based on coa…

Instance Segmentation Object Object Proposal Generation Segmentation+1