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TopX model generates motion for unseen skeletons from text

By PulseAugur Editorial · [1 sources] ·

Researchers have developed TopX, a novel transformer model capable of generating motion for unseen skeletons based solely on text descriptions. This 73M-parameter model utilizes a flow-matching approach and a unique attention mechanism that factors over joints and frames, allowing it to adapt to any kinematic tree topology. TopX was evaluated using SkelShift, a new dataset comprising over 143,000 captioned motion clips, demonstrating improved performance over existing models like UniMate in generating realistic motion for novel characters. AI

IMPACT This research could enable more flexible and adaptable character animation in creative industries by allowing motion generation for novel character rigs.

RANK_REASON The cluster contains a research paper detailing a new model and dataset. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

TopX model generates motion for unseen skeletons from text

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The cluster contains a research paper detailing a new model and dataset. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Tengjiao Sun, Pengcheng Fang, Xiaoyu Zhan, Dongjie Fu, Xiaohao Cai, Hansung Kim ·

    TopX: Text-to-Motion for Unseen Skeletons from the Skeleton File Alone

    arXiv:2610.34321v1 Announce Type: new Abstract: 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 cha…

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