arXiv (All)
open access
HGGT: Robust and Flexible 3D Hand Mesh Reconstruction from Uncalibrated Images
Recovering high-fidelity 3D hand geometry from images is a critical task in computer vision, holding significant value for domains such as robotics, animation and VR/AR. Crucially, scalable applications demand both accuracy and deployment flexibility, requiring the ability to leverage massive amount
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- OmniHands: Towards Robust 4D Hand Mesh Recovery via A Versatile Transformer#141643
- MINT: A Unified Model for World-Space Camera and Hand Motion Estimation from Scalable Egocentric Pipeline Supervision#985280
- Grasp in Gaussians: Fast Monocular Reconstruction of Dynamic Hand-Object Interactions#677567
- Grasp in Gaussians: Fast Monocular Reconstruction of Dynamic Hand-Object Interactions#674368
- OC-GS: Gaussian Splatting for Irregular Turntable Capture#1106271
Record · ID 973100
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive