Fig.1 - U2Net Architecture
- U2-Net is a two-level nested U-structure architecture. It uses a novel ReSidual U-block (RSU) module to extract multi-scale features without degrading resolution, allowing the network to go deeper and attain high resolution without significantly increasing memory and computation cost.
- used for for salient object detection, image segmentation, Image Matting, background removal and other image2image modeling tasks.
Fig.2 - UNet or RSU Block
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U-Net is a U-shaped encoder-decoder architecture with residual connections between each layers. It captures contextual information and intricate detail.
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These U-Net blocks in U2Net architecture are called ReSidual U-block or RSU.
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Example: we have trained an Image Matting model on P3M-10k dataset, and the results are given below.
Fig.3 - Image Matting with U2-Net example
