Salient Object Detection
222 papers with code • 6 benchmarks • 16 datasets
In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).
We further design a feature aggregation module (FAM) to make the coarse-level semantic information well fused with the fine-level features from the top-down pathway.
Benefiting from the quick development of deep convolutional neural networks, especially fully convolutional neural networks (FCNs), remarkable progresses have been achieved on salient object detection recently.
Furthermore, different from binary cross entropy, the proposed PPA loss doesn't treat pixels equally, which can synthesize the local structure information of a pixel to guide the network to focus more on local details.
HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS
The decoder part is inspired by the Cascaded Partial Decoder, known for fast and accurate salient object detection.