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Datasets/NYUv2

NYUv2

NYU-Depth V2

RGB-DUnknownIntroduced 2012-01-01

The NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft Kinect. It features:

  • 1449 densely labeled pairs of aligned RGB and depth images
  • 464 new scenes taken from 3 cities
  • 407,024 new unlabeled frames
  • Each object is labeled with a class and an instance number. The dataset has several components:
  • Labeled: A subset of the video data accompanied by dense multi-class labels. This data has also been preprocessed to fill in missing depth labels.
  • Raw: The raw RGB, depth and accelerometer data as provided by the Kinect.
  • Toolbox: Useful functions for manipulating the data and labels.

Source: https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html Image Source: https://cs.nyu.edu/~silberman/datasets/nyu_depth_v2.html

Benchmarks

3D/mIoU3D Reconstruction/mIoU3D Scene Reconstruction/mIoU3D Semantic Scene Completion/mIoUMulti-Task Learning/Mean IoUReconstruction/mIoUSingle-View 3D Reconstruction/mIoUTransfer Learning/Mean IoU

Statistics

Papers
986
Benchmarks
8

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Tasks

3D3D Object Detection3D Reconstruction3D Scene Reconstruction3D Semantic Scene Completion3D Semantic Scene Completion from a single RGB imageBoundary DetectionDepth CompletionDepth EstimationInstance SegmentationMonocular Depth EstimationMulti-Task LearningPanoptic SegmentationPlane Instance SegmentationReal-Time Semantic SegmentationReconstructionScene Classification (unified classes)Scene SegmentationSemantic SegmentationSingle-View 3D ReconstructionSurface Normal EstimationSurface Normals EstimationTransfer LearningZero-shot Scene Classification (unified classes)