135 datasets found

The UniSeg dataset is used for multi-dataset semantic segmentation with label shifts.

Human parsing has recently attracted a huge amount of interests and achieved great progress with the advance of deep convolutional neural networks and large-scale datasets. Most...

The SUNCG dataset is a large dataset of 3D indoor scenes with missing objects. The dataset is used to evaluate the performance of scene augmentation and context-based object...

The WeatherProof Dataset is a semantic segmentation dataset with accurate clear and adverse weather image pairs for better consistency loss in training and evaluation.

A dataset for carpet defect detection using transfer learning and semantic segmentation.

The FreDSNet dataset is a dataset for joint monocular depth estimation and semantic segmentation from single equirectangular panoramas.

A large-scale face image dataset that contains real face images and corresponding semantic segmentation map, sketch, and textual descriptions.

This paper addresses fast semantic segmentation on video. The dataset used is Cityscapes and CamVid.

A large-scale indoor dataset containing 360-degree fisheye images.

The OmniScape 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...

A dataset for urban scene understanding, containing 360-degree fisheye images with annotations for various tasks.

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.