The NLPR dataset for salient object detection consists of 1,000 image pairs captured by a standard Microsoft Kinect with a resolution of 640×480. The images include indoor and outdoor scenes (e.g., offices, campuses, streets and supermarkets).
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The Light Field Saliency Database (LFSD) contains 100 light fields with 360×360 spatial resolution. A rough focal stack and an all-focus image are provided for each light field. The images in this dataset usually have one salient foreground object and a background with good color contrast.
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NJU2K is a large RGB-D dataset containing 1,985 image pairs. The stereo images were collected from the Internet and 3D movies, while photographs were taken by a Fuji W3 camera.
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The Salient Person dataset (SIP) contains 929 salient person samples with different poses and illumination conditions.
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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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