124 datasets found

The SynWoodScape dataset consists of 10,000 annotated images captured from four different view angles: Front View (FV), Mirror-View Right (MVR), Mirror-View Left (MVL), and Rear...

The Vaihingen dataset consists of 1440 scenes with a size of 250×250 pixels. Each scene is a colour-infrared (CIR) true orthophoto and a height grid (digital surface model; DSM)...

ChainerCV supports algorithms to solve tasks in the computer vision field such as object detection, while considering usability and predictable performance as the top priorities.

Semantic segmentation is a fundamental task in computer vision and enables many downstream applications. It is related to image classification since it produces per-pixel...

Real-time semantic segmentation plays an important role in practical applications such as self-driving and robots. Most semantic segmentation research focuses on improving...

The Synthia dataset is a large-scale urban scene understanding dataset, containing 9000 samples. It is used for semantic segmentation tasks.

The dataset used in the paper is ADE20K for semantic segmentation.

The dataset used in the paper for future semantic segmentation prediction.

A dataset for semantic amodal segmentation, consisting of images with semantic object labels.

The NYUD-v2 dataset is a benchmark for indoor scene segmentation and depth estimation. It contains 1449 images with 4 tasks: semantic segmentation, depth estimation, surface...

The Hyper-Kvasir→Piccolo task is a domain adaptation task for semantic segmentation, where the source domain is Hyper-Kvasir and the target domain is Piccolo.

The Synthia→Cityscapes task is a domain adaptation task for semantic segmentation, where the source domain is Synthia and the target domain is Cityscapes.

The dataset used in this paper for occluded apple tree segmentation.

The Cityscapes validation set is a subset of the Cityscapes dataset, containing 500 finely annotated images.

Semantic segmentation is one of the most fundamental tasks that aims to classify every pixel of a given image into a specific class. It is widely applied to many applications...

The dataset used for experiments on generic image retrieval, person re-identification, and low-shot semantic segmentation.

The internal dataset contains 6 million real-world driving scenarios from Las Vegas (LV), Seattle (SEA), San Francisco (SF), and the campus of the Stanford Linear Accelerator...

The proposed framework for crack semantic segmentation.

The proposed framework for road semantic segmentation.

A dataset for free space detection using a single fisheye camera