150 datasets found

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  • NYUv2

    Multi-task learning (MTL) research is broadly divided into two categories: one is to learn the correlation between tasks through model structures, and the other is to balance...

  • C3: Concentrated-Comprehensive Convolution and its application to semantic se...

    The proposed Concentrated-Comprehensive Convolution (C3) block for lightweight semantic segmentation.

  • SYNTHIA → Cityscapes

    The SYNTHIA dataset is a synthetic dataset for semantic segmentation, and the Cityscapes dataset is a real-world dataset for semantic segmentation.

  • GTA5 → Cityscapes

    The GTA5 dataset is a synthetic dataset for semantic segmentation, and the Cityscapes dataset is a real-world dataset for semantic segmentation.

  • PASCAL VOC 2007 dataset

    PASCAL VOC 2007 dataset is a widely used dataset for object detection and semantic segmentation. We use all the split sets (training, validation, testing) in the VOC2007 dataset...

  • Syntagen - Harnessing Generative Models for Synthetic Visual Datasets

    The dataset is generated using a latent diffusion model, specifically Stable Diffusion 2.1, and is used for semantic segmentation tasks.

  • Replica

    The Replica dataset contains 18 various highly photo-realistic indoor environments. It provides dense-mesh, high-resolution RGBD images and a large range of instance annotations...

  • ScanNet Dataset

    The ScanNet dataset is a large-scale indoor dataset composed of monocular sequences with ground truth poses and depth images.

  • Gaofen Image Dataset (GID)

    A dataset for semantic segmentation of high-resolution remote sensing images.

  • ISPRS Potsdam dataset

    A benchmark dataset for semantic segmentation of high-resolution remote sensing images.

  • SemanticPOSS

    A point cloud dataset with large quantity of dynamic instances, consisting of 2,988 real-world scans with point-level annotations.

  • LoveDA

    The LoveDA dataset contains high-spatial-resolution images from three different cities, focusing on improving the generalization capability of model from different urban and...

  • LoveDA Urban

    Semantic segmentation of remote sensing imagery generally revolves two primary approaches: pixel-based and object-based methods.

  • ISPRS Vaihingen

    The ISPRS Vaihingen dataset consists of remotely sensed imagery with a spatial resolution of 9 centimeters, and includes 6 semantic classes.

  • Pascal VOC

    Semantic segmentation is a crucial and challenging task for image understanding. It aims to predict a dense labeling map for the input image, which assigns each pixel a unique...

  • HomebrewedDB

    A real-world dataset for multi-object shape completion, featuring 33 objects (e.g., toy, household, and industrial objects).

  • YCB-Video

    The dataset used for 6D object pose estimation, consisting of images of 16 objects with varying levels of occlusion.

  • TrashNet

    The TrashNet dataset contains images of waste, focusing on recycling waste classification.

  • COCO Dataset

    The COCO dataset is a large-scale dataset for object detection, semantic segmentation, and captioning. It contains 80 object categories and 1,000 image instances per category,...

  • ADE20k

    Semantic segmentation is one of the fundamental prob-lems in computer vision, whose task is to assign a seman-tic label to each pixel of an image so that different classes can...