Object Detection Models


Introduced by Liu et al. in Path Aggregation Network for Instance Segmentation

Path Aggregation Network, or PANet, aims to boost information flow in a proposal-based instance segmentation framework. Specifically, the feature hierarchy is enhanced with accurate localization signals in lower layers by bottom-up path augmentation, which shortens the information path between lower layers and topmost feature. Additionally, adaptive feature pooling is employed, which links feature grid and all feature levels to make useful information in each feature level propagate directly to following proposal subnetworks. A complementary branch capturing different views for each proposal is created to further improve mask prediction.

Source: Path Aggregation Network for Instance Segmentation


Paper Code Results Date Stars


Task Papers Share
Object Detection 3 14.29%
Semantic Segmentation 3 14.29%
Instance Segmentation 2 9.52%
Face Sketch Synthesis 1 4.76%
Crowd Counting 1 4.76%
Anatomy 1 4.76%
Vehicle Re-Identification 1 4.76%
Demosaicking 1 4.76%
Denoising 1 4.76%