hand-object pose
16 papers with code • 2 benchmarks • 4 datasets
6D pose estimation of hand and object
Libraries
Use these libraries to find hand-object pose models and implementations
HO-3D
DexYCB
ARCTIC
Human Palm and Gloves Dataset | Human Body Parts Dataset
Most implemented papers
HOnnotate: A method for 3D Annotation of Hand and Object Poses
This dataset is currently made of 77, 558 frames, 68 sequences, 10 persons, and 10 objects.
Learning joint reconstruction of hands and manipulated objects
hassony2/manopth
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CVPR 2019
Previous work has made significant progress towards reconstruction of hand poses and object shapes in isolation.
ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesis
mvig-sjtu/artiboost
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CVPR 2022
In contrast, data synthesis can easily ensure those diversities separately.
AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstruction
zerchen/AlignSDF
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We show that such aligned SDFs better focus on reconstructing shape details and improve reconstruction accuracy both for hands and objects.
Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands
The hand's point cloud is pruned and robust global registration is performed to generate object pose hypotheses, which are clustered.
HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation
bardiadoosti/HOPE
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CVPR 2020
Hand-object pose estimation (HOPE) aims to jointly detect the poses of both a hand and of a held object.
Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation
shreyashampali/kypt_transformer
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CVPR 2022
We propose a robust and accurate method for estimating the 3D poses of two hands in close interaction from a single color image.
Towards unconstrained joint hand-object reconstruction from RGB videos
hassony2/homan
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Our work aims to obtain 3D reconstruction of hands and manipulated objects from monocular videos.
Enhancing Generalizable 6D Pose Tracking of an In-Hand Object with Tactile Sensing
When manipulating an object to accomplish complex tasks, humans rely on both vision and touch to keep track of the object's 6D pose.
A new benchmark for group distribution shifts in hand grasp regression for object manipulation. Can meta-learning raise the bar?
dubiouscactus/meta-learning-hope
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We propose a novel benchmark for object group distribution shifts in hand and object pose regression.
