PASCAL-S is a dataset for salient object detection consisting of a set of 850 images from PASCAL VOC 2010 validation set with multiple salient objects on the scenes.
179 PAPERS • 3 BENCHMARKS
The Extended Complex Scene Saliency Dataset (ECSSD) is comprised of complex scenes, presenting textures and structures common to real-world images. ECSSD contains 1,000 intricate images and respective ground-truth saliency maps, created as an average of the labeling of five human participants.
164 PAPERS • 3 BENCHMARKS
HKU-IS is a visual saliency prediction dataset which contains 4447 challenging images, most of which have either low contrast or multiple salient objects.
136 PAPERS • 3 BENCHMARKS
The DUT-OMRON dataset is used for evaluation of Salient Object Detection task and it contains 5,168 high quality images. The images have one or more salient objects and relatively cluttered background.
120 PAPERS • 2 BENCHMARKS
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 collected from the ImageNet DET test set and the SUN data set. Both the training and test set contain very challenging scenarios for saliency detection. Accurate pixel-level ground truths are manually annotated by 50 subjects.
114 PAPERS • 4 BENCHMARKS
Includes 4000 images; 200 from each of 20 categories covering different types of scenes such as Cartoons, Art, Objects, Low resolution images, Indoor, Outdoor, Jumbled, Random, and Line drawings.
43 PAPERS • 1 BENCHMARK
iSUN is a ground truth of gaze traces on images from the SUN dataset. The collection is partitioned into 6,000 images for training, 926 for validation and 2,000 for test.
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Lytro Illum is a new light field dataset using a Lytro Illum camera. 640 light fields are collected with significant variations in terms of size, textureness, background clutter and illumination, etc. Micro-lens image arrays and central viewing images are generated, and corresponding ground-truth maps are produced.
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HS-SOD is a hyperspectral salient object detection dataset with a collection of 60 hyperspectral images with their respective ground-truth binary images and representative rendered colour images (sRGB).
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ReDWeb-S is a large-scale challenging dataset for Salient Object Detection. It has totally 3179 images with various real-world scenes and high-quality depth maps. The dataset is split into a training set with 2179 RGB-D image pairs and a testing set with the remaining 1000 image pairs.
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