2015

Instance-aware Semantic Segmentation via Multi-task Network Cascades

Dai, Jifeng, He, Kaiming, Sun, Jian

Understand

Semantic segmentation research has recently witnessed rapid progress, but many leading methods are unable to identify object instances.

In this paper, we present Multi-task Network Cascades for instance-aware semantic segmentation.
Our model consists of three networks, respectively differentiating instances, estimating masks, and categorizing objects.
These networks form a cascaded structure, and are designed to share their convolutional features.

Built on

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