Keyword [DeepLabv3+] [Encoder-Decoder] [Xception]
Chen L C, Zhu Y, Papandreou G, et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[C]//Proceedings of the European conference on computer vision (ECCV). 2018: 801-818.
1. Overview
In this paper, it proposes DeepLabv3+ by extending DeepLabv3.
- Encoder-Decoder structure.
- Adapt Xception model.
- Apply Depthwise Separable Conv.
1.1. Architecture
1) Encoder output: last feature map before logits in the DeepLabv3.
2) Apply $1 \times 1$ Conv on low-level features to reduce the number of channels, since large channels may ignore encoder output.
1.2. Xception
Make a few changes:
1) Deeper Xception.
2) Replace all MaxPool with Depthwise Separable Conv (with strides), which enables to apply Atrous Separable Conv.
3) After each $3 \times 3$ Depthwise Conv, add BN-ReLU.
1.3. Comparison
