25 datasets found

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  • Interiornet

    Interiornet: Mega-scale multi-sensor photo-realistic indoor scenes dataset.

  • SUNCG

    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...

  • iGibson dataset

    The iGibson dataset is a large-scale indoor scene dataset, consisting of 572 buildings, 1400 floors, and 211,000 square meters of indoor space.

  • THEODORE

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

  • NYUD-v2

    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...

  • Scenenet RGB-D: 5M photorealistic images of synthetic indoor trajectories wit...

    Scenenet RGB-D: 5M photorealistic images of synthetic indoor trajectories with ground truth

  • Matterport3D dataset

    The Matterport3D dataset contains scans of real-world environments such as apartments, offices, and churches.

  • NYUD2

    NYUD2 dataset is a dataset containing RGB-D images for indoor scene understanding. It is used for depth estimation and semantic segmentation tasks.

  • Matterport3D: Learning from RGB-D Data in Indoor Environments

    A large-scale dataset of indoor 3D scenes with semantic annotations.

  • 2D-3D-S dataset

    The 2D-3D-S dataset is an indoor dataset with multiple modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations.

  • New York University Dataset

    A dataset for indoor scene understanding, containing 1449 RGBD images.

  • SceneNet RGB-D

    The dataset used in this paper for multi-sensor next-best-view planning as matroid-constrained submodular maximization.

  • ARKITScenes

    ARKITScenes: A diverse real-world dataset for 3D indoor scene understanding using mobile RGB-D data

  • PanoContext

    The dataset used in the paper is a collection of spherical panoramas for indoor scene understanding tasks.

  • Stanford S3DIS

    The Stanford S3DIS dataset is a large-scale indoor dataset containing point clouds and semantic labels.

  • SUN-RGBD

    The dataset is used for indoor scene understanding and contains RGB and depth images.

  • NYU-DepthV2

    The NYU-DepthV2 dataset is an indoor scene dataset that consists of RGB and depth images.

  • 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...

  • 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.