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Kirin framework reconstructs 3D animal motion from video, creates large dataset

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced Kirin, a framework designed to reconstruct 3D animal motion from video, learn motion priors at scale, and generate realistic motion for animating 3D meshes. This work addresses the scarcity of high-quality animal motion data by creating AiM3D, the first large-scale dataset of aligned video-text-motion tuples for quadruped animals using in-the-wild videos. The framework enables text- and image-conditioned motion generation across diverse species and can automatically rig and animate 3D meshes with the generated motion, paving the way for advanced animal animation. AI

IMPACT Enables more realistic and diverse animal animations by providing a scalable method for motion generation and a large-scale dataset.

RANK_REASON The cluster describes a research paper detailing a new framework and dataset for animal motion generation.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Kirin framework reconstructs 3D animal motion from video, creates large dataset

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The cluster describes a research paper detailing a new framework and dataset for animal motion generation.
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COVERAGE [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Kirin: Animal Motion Generation from In-the-Wild Video

    Kirin reconstructs 3D animal motion from video to build a large-scale dataset and generate text- and image-conditioned motion for animating 3D meshes.

  2. arXiv cs.CV TIER_1 English(EN) · Brian Nlong Zhao, Zhuoyang Pan, James M. Rehg, Jiajun Wu, Shangzhe Wu ·

    Kirin: Animal Motion Generation from In-the-Wild Video

    arXiv:2609.01823v1 Announce Type: new Abstract: Understanding animal motion is fundamental to modeling animal behavior and biomechanics, yet progress in this area lags far behind human motion research due to the scarcity of high-quality motion data. While human motion can be capt…

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