Large dataset of hand-object contact, hand- and object-pose, and 2.9 M RGB-D grasp images.
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Updated
Oct 28, 2022 - Jupyter Notebook
Large dataset of hand-object contact, hand- and object-pose, and 2.9 M RGB-D grasp images.
GrabNet: A Generative model to generate realistic 3D hands grasping unseen objects (ECCV2020)
GRAB: A Dataset of Whole-Body Human Grasping of Objects
[CVPR 2023] Official repository for downloading, processing, visualizing, and training models on the ARCTIC dataset.
[CVPR 2022 Oral] ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis
ContactGen: Generative Contact Modeling for Grasp Generation (ICCV 2023)
[CVPR 2022] OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction
[CVPR 2024✨Highlight] Official repository for HOLD, the first method that jointly reconstructs articulated hands and objects from monocular videos without assuming a pre-scanned object template and 3D hand-object training data.
[WACV2023] Interacting Hand-Object Pose Estimation via Dense Mutual Attention
[ECCV 2022] SAGA: Stochastic Whole-Body Grasping with Contact
AffordPose: A Large-scale Dataset of Hand-Object Interactions with Affordance-driven Hand Pose (ICCV 2023)
Code implementation for paper titled "HOI-Ref: Hand-Object Interaction Referral in Egocentric Vision"
[NeurIPS 2022 Spotlight] Hand-Object Interaction Image Generation
Simple 3D rendering of hand-object interactions for the ARCTIC dataset
[CVPR 2024] HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields
SHOWMe: Benchmarking Object-agnostic Hand-Object 3D Reconstruction (Dataset, Contains proposed top baseline reconstructions with estimated camera poses)
hand-object contact models for ContactPose
This is a repository for GraspXL, which can generate objective-drive grasping motions for 500k+ objects with different dexterous hands.
Entry point for ContactGrasp code system.
Code for experiments of the paper "A new benchmark for group distribution shifts in hand grasp regression for object manipulation. Can meta-learning raise the bar?" (DistShift workshop, NeurIPS 2022).
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