The Common Objects in COntext-stuff (COCO-stuff) dataset is a dataset for scene understanding tasks like semantic segmentation, object detection and image captioning. It is constructed by annotating the original COCO dataset, which originally annotated things while neglecting stuff annotations. There are 164k images in COCO-stuff dataset that span over 172 categories including 80 things, 91 stuff, and 1 unlabeled class. Source: Image Colorization: A Survey and Dataset Image Source: https://github.com/nightrome/cocostuff
SketchyCOCO dataset consists of two parts: Object-level data Object-level data contains $20198(train18869+val1329)$ triplets of {foreground sketch, foreground image, foreground edge map} examples covering 14 classes, $27683(train22171+val5512)$ pairs of {background sketch, background image} examples covering 3 classes. Scene-level data Scene-level data contains $14081(train 11265 + val 2816)$ pairs of {foreground image&background sketch, scene image} examples, $14081(train 11265 + val 2816)$ pairs of {scene sketch, scene image} examples and the segmentation ground truth for $14081(train 11265 + val 2816)$ scene sketches. Some val scene images come from the train images of the COCO-Stuff dataset for increasing the number of the val images of the SketchyCOCO dataset. Source: https://github.com/sysu-imsl/SketchyCOCO Image source: https://arxiv.org/pdf/2003.02683v5.pdf
Scribble is a new outline dataset consisting of 200 images (150 train, 50 test) for each of 10 classes – basketball, chicken, cookie, cupcake, moon, orange, soccer, strawberry, watermelon and pineapple. All the images have a white background and were collected using search keywords on popular search engines. In each image, we obtain rough outlines for the image. We find the largest blob in the image after thresholding it into a black and white image. We fill the interior holes of the largest blob and obtain a smooth outline using the SavitzkyGolay filter. Source: https://arxiv.org/pdf/1909.11081v2.pdf
FS2K is a high-quality Facial Sketch Synthesis (FSS). It consists of 2,104 image-sketch pairs spanning three types of sketch styles, image backgrounds, lighting conditions, skin colors, and facial attributes. FS2K differs from previous FSS datasets in difficulty, diversity, and scalability, and should thus facilitate the progress of FSS research.
SKSF-A consists of seven distinct styles drawn by professional artists. SKSF-A contains 134 identities and corresponding sketches, making a total of 938 face-sketch pairs. SKSF-A is introduced in StyleSketch, Eurographics 2024. https://kwanyun.github.io/stylesketch_project/