Methods › Computer Vision › Semantic Segmentation Modules › Pyramid Pooling Module

Pyramid Pooling Module

75 papers tagged archive 2025-07-28

Introduced by Hengshuang Zhao et al. in Pyramid Scene Parsing Network

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

A Pyramid Pooling Module is a module for semantic segmentation which acts as an effective global contextual prior. The motivation is that the problem of using a convolutional network like a ResNet is that, while the receptive field is already larger than the input image, the empirical receptive field is much smaller than the theoretical one especially on high-level layers. This makes many networks not sufficiently incorporate the momentous global scenery prior.

The PPM is an effective global prior representation that addresses this problem. It contains information with different scales and varying among different sub-regions. 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.

PaperSource

Papers archive 2025-07-28

30 shown of 75, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 81 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Semantic Segmentation61
Segmentation38
Decoder13
Image Segmentation12
Autonomous Driving9
Object8
Instance Segmentation7
Scene Parsing7
Image Classification6
Object Detection6
Real-Time Semantic Segmentation6
object-detection6
Scene Understanding5
Video Semantic Segmentation4
image-classification4
Deep Learning3
Few-Shot Semantic Segmentation3
Knowledge Distillation3
Lesion Segmentation3
Self-Driving Cars3

Usage over time archive 2025-07-28

Papers per year tagged with Pyramid Pooling Module: 2016 to 2025, peak 12 12 0 2016: 1 paper 2016 2017: 1 paper 2017 2018: 11 papers 2018 2019: 7 papers 2019 2020: 9 papers 2020 2021: 12 papers 2021 2022: 10 papers 2022 2023: 10 papers 2023 2024: 10 papers 2024 2025: 4 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (75 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Semantic Segmentation Modules

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