hold
Enrichment pending[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
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Overview
[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.
Capability facts
- Languages
- python
Source: github.language · Jul 11, 2026
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README
Getting started
Get a copy of the code:
git clone https://github.com/zc-alexfan/hold.git
cd hold; git submodule update --init --recursive
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Setup environments
- Follow the instructions here:
docs/setup.md. - You may skip external dependencies for now.
- Follow the instructions here:
-
Train on a preprocessed sequence
- Start with one of our preprocessed in-the-wild sequences, such as
hold_bottle1_itw. - Familiarize yourself with the usage guidelines in
docs/usage.mdfor this preprocessed sequence. - This will enable you to train, render HOLD, and experiment with our interactive viewer.
- At this stage, you can also explore the HOLD code in the
./codedirectory.
- Start with one of our preprocessed in-the-wild sequences, such as
-
Set up external dependencies and process custom videos
- After understanding the initial tools, set up the "external dependencies" as outlined in
docs/setup.md. - Preprocess the images from the
hold_bottle1_itwsequence by following the instructions indocs/custom.md. - Train on this sequence to learn how to build a custom dataset.
- You can capture your own custom video and reconstruct it in 3D at this point.
- Most preprocessing artifact files are documented in
docs/data_doc.md, which you can use as a reference.
- After understanding the initial tools, set up the "external dependencies" as outlined in
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Two-hand setting: Bimanual category-agnostic reconstruction
- At this point, you can preprocess and train on a custom single-hand sequence.
- Now you can take on the bimanual category-agnostic reconstruction challenge!
- Following the instruction in
docs/arctic.mdto reconstruct two-hand manipulation of ARCTIC sequences.