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hold

zc-alexfan/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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493 stars18 forksLast push Mar 10, 2026 Python MIT

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
PyPI

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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

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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...

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