Yana Hasson, Gül Varol, Dimitris Tzionas, Igor Kalevatykh, Michael J. Black, Ivan Laptev, Cordelia Schmid, CVPR 2019

• Project page
• Training code and model
• GraspIt grasps generation using MANO
• Dataset generation

• Request the dataset on the ObMan webpage. Note that the data falls under the following license
• unzip obman.zip to /path/to/obman
• Your dataset structure should look like

obman/
  test/
    rgb/
    rgb_obj/
    meta/
    ...
  val/
    rgb/
    rgb_obj/
    meta/
    ...

• Download object models from ShapeNet
  • Create an account on shapenet.org
  • Download models from download page

git clone https://github.com/hassony2/obman

cd obman

python readataset --root /path/to/obman --shapenet_root /path/to/ShapeNetCore.v2 --split test --viz

Options you might be interested in --segment which keeps only the foreground --mini_factor 0.01 to load only 1% of the data (to speed-up loading)

Sample points on the external surface of the object:

python shapenet_samplepoints.py

Hand vertices in blue, object vertices in red.

If you find this dataset useful for your research, consider citing:

@INPROCEEDINGS{hasson19_obman,
  title     = {Learning joint reconstruction of hands and manipulated objects},
  author    = {Hasson, Yana and Varol, G{\"u}l and Tzionas, Dimitris and Kalevatykh, Igor and Black, Michael J. and Laptev, Ivan and Schmid, Cordelia},
  booktitle = {CVPR},
  year      = {2019}
}