Feature Pyramid Grids, or FPG, is a deep multi-pathway feature pyramid, that represents the feature scale-space as a regular grid of parallel bottom-up pathways which are fused by multi-directional lateral connections. It connects the backbone features, $C$, of a ConvNet with a regular structure of $p$ parallel top-down pyramid pathways which are fused by multi-directional lateral connections, AcrossSame, AcrossUp, AcrossDown, and AcrossSkip. AcrossSkip are direct connections while all other types use convolutional and ReLU layers.
On a high-level, FPG is a deep generalization of FPN from one to $p$ pathways under a dense lateral connectivity structure.
Source: Feature Pyramid GridsPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Image Classification | 1 | 16.67% |
Medical Image Classification | 1 | 16.67% |
Skin Lesion Classification | 1 | 16.67% |
Continuous Control | 1 | 16.67% |
Object Detection | 1 | 16.67% |
Object Recognition | 1 | 16.67% |