arXiv (All)
open access
Praxis: Distilling Physical Interaction Priors from Egocentric Videos for Generalizable Whole-Body Manipulation
Mobile humanoid manipulation requires both reaching a usable workspace and preserving precise hand-object interactions as object poses and contact conditions change. Learning these behaviors from limited task-specific data remains challenging. To bridge this gap, we introduce Praxis, a whole-body ma
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
- GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors#258658
- HumanEgo: Zero-Shot Robot Learning from Minutes of Human Egocentric Videos#1110251
- From Pixel to Poses: Object-centric Tool Manipulation Learning from Human Demonstrations#1129966
- Bridging Handheld and Teleoperated Supervision for Contact-Rich Manipulation via State-Gated Experts#1049891
- UMI-Bridge: Action-Anchored Latent Alignment across Human and Robot Manipulation Data#1012432
Record · ID 1105294
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