Pyramid Pooling Module
The Pyramid Pooling Module (PPM) is a crucial component in the architecture of PSPNet, designed to capture global contextual information effectively. It operates at multiple scales, fusing features from different sub-regions, and provides an effective global contextual prior for pixel-level scene parsing in the PSPNet architecture.
Pyramid Pooling Operation
- The Pyramid Pooling Module fuses features under four different pyramid scales (1×1, 2×2, 3×3, and 6×6).
- The coarsest level (highlighted in red) involves global pooling, generating a single bin output.
- Subsequent levels separate the feature map into different sub-regions and form pooled representations for different locations.
- Each pyramid level’s dimension is reduced using 1×1 convolution layers to maintain the weight of global features.
- Low-dimensional feature maps are upsampled via bilinear interpolation to match the original feature map size.
- Finally, different levels of features are concatenated to form the final pyramid pooling global feature.
PSPNet (Pyramid Scene Parsing Network) for Image Segmentation
Within the intricate landscape of semantic segmentation, the Pyramid Scene Parsing Network or PSPNet has emerged as a formidable architecture by showcasing unparalleled performance in deciphering intricate scenes. In this article, we will discuss about PSPNet and implement it.