hold
Method for joint reconstruction of articulated hands and objects from monocular videos
GraphCanon updated Sep 24, 2026 · GitHub synced Sep 24, 2026
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Decision brief
HOLD for monocular video analysis of hand-object interactions without prior object models.
Good fit when
- When no prior knowledge of object shapes is available but joint 3D reconstruction of hands manipulating objects from single-view videos is needed
- For research projects requiring category-agnostic bimanual interaction reconstruction from custom captured sequences
Avoid when
- If there are pre-scanned object models that could enhance accuracy beyond self-reconstruction capabilities
- In scenarios where the computational resources for preprocessing and training on custom datasets are insufficient
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (197d since push)
- As of Sep 24, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 24, 2026
- Security (OSV)
- 9 low (9 low)
- As of Jul 11, 2026
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Install
pip install hold PyPISimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
The HOLD method enables the 3D reconstruction of articulated hand-object interactions from single-view video inputs without needing prior object models or labeled 3D training data.
Capability facts
- Languages
- python
Source: github.language · Sep 24, 2026
Categories
Tags
README
Getting started Get a copy of the code: 1. Setup environments Follow the instructions here: . You may skip external dependencies for now. 1. Train on a preprocessed sequence Start with one of our preprocessed in the wild sequences, such as . Familiarize yourself with the usage gu...
For agents
This page has a .md twin and JSON over the API.