Salient Object Detection
133 papers with code • 5 benchmarks • 13 datasets
We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e. g., CIFAR-100 and ImageNet.
Ranked #6 on RGB Salient Object Detection on PASCAL-S
In this paper, we design a simple yet powerful deep network architecture, U$^2$-Net, for salient object detection (SOD).
Ranked #1 on Salient Object Detection on HKU-IS
In this paper, we propose a predict-refine architecture, BASNet, and a new hybrid loss for Boundary-Aware Salient object detection.
Ranked #1 on Salient Object Detection on DUTS-TE
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.
Ranked #1 on RGB Salient Object Detection on SOD
In the second step, we integrate the local edge information and global location information to obtain the salient edge features.
Ranked #2 on Co-Salient Object Detection on CoSOD3k
In this paper, we propose a novel Cascaded Partial Decoder (CPD) framework for fast and accurate salient object detection.
Ranked #1 on RGB Salient Object Detection on ISTD
Recent progress on saliency detection is substantial, benefiting mostly from the explosive development of Convolutional Neural Networks (CNNs).
Ranked #4 on RGB Salient Object Detection on SBU
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.
Ranked #5 on Medical Image Segmentation on Kvasir-SEG
Salient object detection models often demand a considerable amount of computation cost to make precise prediction for each pixel, making them hardly applicable on low-power devices.