Lixin Yang (杨理欣)
Anran Xu (徐安然)
Description: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction
dataset (50) hand-object interaction (2)
To ensure latest version, please use sha256sum to calculate the checksum of the anno_v2.1.zip . You will get:
$ sha256sum anno_v2.1.zip --tag SHA256 (anno_v2.1.zip) = dc64402d65cff3c1e2dd40fb560fcc81e3757e1936f44d353c381874489d71ea. OakInk-Shape -- Geometry-based dataset Meta files for organizing and indexing the objects: metaV2.zip (15K) All hand parameters (pose, shape, root transf): oakink_shape_v2.zip (46M) All the real object models: OakInkObjectsV2.zip (1G) All the virtual object models: OakInkVirtualObjectsV2.zip (1G) After downloading all the above .zip files, you need to arrange them in the following struc
OakInk-Image provides data splits for two categories of tasks: Hand Mesh Recovery and Hand-Object Pose Estimation . The dataset contains in total 314,404 frames if no filtering is applied, in which 157,600 frames are from two-hand sequences. For single view tasks, we filter out frames that have less than 50% of joints falling in the bounds of the images. Note these frames might still be useful in multiview tasks. Refer to oikit repo for the usage of these split files.
Lixin Yang (杨理欣)
Anran Xu (徐安然)