arXiv (All)
open access
TopX: Text-to-Motion for Unseen Skeletons from the Skeleton File Alone
Text-to-motion models generate for the skeletons they were trained on, while a new character arrives as a skeleton file and nothing else. We study text-to-motion for skeletons that no training clip has used, with no clips of the character, no template, no retargeting and no fine-tuning. We present T
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
- A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting#677568
- A Unified Conditional Flow for Motion Generation, Editing, and Intra-Structural Retargeting#674369
- KinoGen: Customizable Humanoid Loco-Manipulation References via Kinematically Grounded Video Generation#1355470
- Streaming Multi-Track Timeline Control for 3D Human Motion Generation#1199147
- Blendshape Generation for Models with Disconnected Parts: Adding ARKit/MediaPipe Blendshapes to Anime-Style Character Models#1458546
Record · ID 1457475
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