DUTS is a saliency detection dataset containing 10,553 training images and 5,019 test images. All training images are collected from the ImageNet DET training/val sets, while test images are …

Jan 22, 2018 · Accurate pixel-level ground truths are manually annotated by 50 subjects. To our knowledge, DUTS is currently the largest saliency detection benchmark with the explicit …

Sep 4, 2024 · DUTS-MQ consists of approximately 100K image-mask pairs with human-annotated preference scores, enabling the learning of real human preferences in measuring mask …

Oct 25, 2022 · In this paper, we propose a novel yet effective method for SOD, coined SODGAN, which can generate infinite high-quality image-mask pairs requiring only a few labeled data, …

Jan 22, 2018 · DUTS is a large-scale dataset comprising 10,553 train images and 5,019 test images. The training images are sourced from the ImageNet DET training/val sets, while the …

The current state-of-the-art on DUTS-TE is BiRefNet (DUTS, HRSOD, UHRSD). See a full comparison of 31 papers with code.

Mar 22, 2022 · To address this issue, we propose a Non-Salient Suppression (NSS) method to optimize the erroneous saliency maps generated in the first round and leverage them for the …

In this paper, we propose a weakly-supervised salient object detection model to learn saliency from such annotations. In doing so, we first relabel an existing large-scale salient object …

HQ version of the DUTS dataset for saliency detection, upscaled using SwinIR and refined by utilising CascadePSP. The refined masks aren't always perfect, but they are pretty good. …

DUTS: a large scale dataset containing 10,553 training images and 5,019 test images