1. 3D Model

1.1. Intro

  • voxel
  • point cloud
  • volume

1.2. Datasets

Target Dataset:

  • SHREC13STB: 1258 models of 90 classes
  • Princeton Shape Benchmark (2003): 1,814 models collected from the web in .OFF format. Used to evaluating shape-based retrieval and analysis algorithms.
    • hierachical label supports clssification of multiple granularities
    • 161 classes each contain at least 4 models at most 100 models

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  • Shapenet 2015: 3Million+ models and 4K+ categories. A dataset that is large in scale, well organized and richly annotated.
  • ObjectNet3D: A Large Scale Database for 3D Object Recognition (2016) :100 categories, 90,127 images, 201,888 objects in these images and 44,147 3D shapes. Tasks: region proposal generation, 2D object detection, joint 2D detection and 3D object pose estimation, and image-based 3D shape retrieval Benchmark:

  • Kinect300: Abstract and noisy

    • a 3D Sketch Dataset, with 300 3D Sketches. 30 classes, each with 10 sketches by utilizing a Kinect-based virtual 3D drawing system
    • format: .off

Example 3D sketches (one example per class, shown in one view) of our Kinect300 dataset. Example 3D models in the targe 3D model dataset of the SHREC13STB benchmark.

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