NOTE: We are aware that the original Dropbox data download links are not valid anymore. Most of the data is now available in IEEE DataPort. This is being tracked in Issue 27.
For users that do not have access to IEEE DataPort, here is a Google Drive link to sample data.
Instructions (assume CONTACTPOSE_ROOT
denotes the ContactPose repository directory):
- Delete or rename the
CONTACTPOSE_ROOT/data
. - Download this ZIP file to
CONTACTPOSE_ROOT
. - Unzip this file. It will create
CONTACTPOSE_ROOT/ContactPose sample data
. Rename this directory toCONTACTPOSE_ROOT/data
.
Download and pre-processing utilities + Python dataloader for the ContactPose dataset. The dataset was introduced in the following ECCV 2020 paper: ContactPose: A Dataset of Grasps with Object Contact and Hand Pose -
Samarth Brahmbhatt, Chengcheng Tang, Christopher D. Twigg, Charles C. Kemp, and James Hays
Example ContactPose data: Contact Maps, 3D hand pose, and RGB-D grasp images for functional grasps.- Explore the dataset
- hand-object contact ML code
- ROS code used for recording the dataset
@InProceedings{Brahmbhatt_2020_ECCV,
author = {Brahmbhatt, Samarth and Tang, Chengcheng and Twigg, Christopher D. and Kemp, Charles C. and Hays, James},
title = {{ContactPose}: A Dataset of Grasps with Object Contact and Hand Pose},
booktitle = {The European Conference on Computer Vision (ECCV)},
month = {August},
year = {2020}
}
We have made some data and annotation corrections. The link above mentions the correction date and the exact data that was corrected. If you got that data before the correction date, please re-download it.
- Code: MIT License
- 3D models: each model has its own license, see
README.txt
andlicenses.json
in the downloads - All other data: MIT License
- 🔲 Create a HuggingFace dataset.
- ✔️ For users that do not have access to IEEE DataPort, here is a Google Drive link to sample data.
- ✔️ Dataset has been uploaded to IEEE DataPort at https://dx.doi.org/10.21227/fb0w-gt48 to prevent Dropbox issues.
- ✔️ Fix annotation errors in data from participants 31-35.
- 🔲 Use rclone for Dropbox downloads
- 🔲 Make depth images optional in cropping script
- ✔️ Robust networking utilities for data download with exponential backoff in case of connection failure
- ✔️ Speed up dataset download by organizing images into videos
- ✔️ Release object 3D models
- ✔️ Code for cropping images around hand-object
- ✔️ Release contact modeling ML code
- 🔲 Release more data analysis code
- ✔️ Release MANO fitting code | demo at end of notebook
- ✔️ RGB-D image background randomization support
- ✔️ new Release ROS code used for recording the dataset
- ✔️ MANO and object mesh rendering
- 🔲 Documentation using Read the Docs