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Methods/PSPNet

PSPNet

Computer VisionIntroduced 200047 papers

Description

PSPNet, or Pyramid Scene Parsing Network, is a semantic segmentation model that utilises a pyramid parsing module that exploits global context information by different-region based context aggregation. The local and global clues together make the final prediction more reliable. We also propose an optimization

Given an input image, PSPNet use a pretrained CNN with the dilated network strategy to extract the feature map. The final feature map size is $1/8$ of the input image. On top of the map, we use the pyramid pooling module to gather context information. Using our 4-level pyramid, the pooling kernels cover the whole, half of, and small portions of the image. They are fused as the global prior. Then we concatenate the prior with the original feature map in the final part of. It is followed by a convolution layer to generate the final prediction map.

Papers Using This Method

Semantic segmentation for building houses from wooden cubes2025-03-28 Optimized Unet with Attention Mechanism for Multi-Scale Semantic Segmentation2025-02-06 Parking Space Detection in the City of Granada2025-01-11 Hyperspectral Imaging-Based Perception in Autonomous Driving Scenarios: Benchmarking Baseline Semantic Segmentation Models2024-10-29 A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation2024-09-26 A Comparative Analysis of CNN-based Deep Learning Models for Landslide Detection2024-08-03 Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic Segmentation2024-07-18 Evaluation of Deep Learning Semantic Segmentation for Land Cover Mapping on Multispectral, Hyperspectral and High Spatial Aerial Imagery2024-06-20 Fuzzy Rank-based Late Fusion Technique for Cytology image Segmentation2024-03-16 Generative Denoise Distillation: Simple Stochastic Noises Induce Efficient Knowledge Transfer for Dense Prediction2024-01-16 A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing2023-12-01 Equirectangular image construction method for standard CNNs for Semantic Segmentation2023-10-13 Evaluation Kidney Layer Segmentation on Whole Slide Imaging using Convolutional Neural Networks and Transformers2023-09-05 Image Segmentation Keras : Implementation of Segnet, FCN, UNet, PSPNet and other models in Keras2023-07-25 SSSegmenation: An Open Source Supervised Semantic Segmentation Toolbox Based on PyTorch2023-05-26 A Simple and Generic Framework for Feature Distillation via Channel-wise Transformation2023-03-23 An End-to-End Two-Phase Deep Learning-Based workflow to Segment Man-made Objects Around Reservoirs2023-02-07 Efficient and Effective Methods for Mixed Precision Neural Network Quantization for Faster, Energy-efficient Inference2023-01-30 A Strong Baseline for Generalized Few-Shot Semantic Segmentation2022-11-25 Road Rutting Detection using Deep Learning on Images2022-09-28