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TopoCap framework animates any 3D character from video

By PulseAugur Editorial · [2 sources] ·

Researchers have developed TopoCap, a novel framework for generating animations from monocular video that can adapt to any skeletal structure. This system learns a universal motion manifold, disentangling motion dynamics from specific topologies. It utilizes a Graph CVAE and conditional flow matching to predict topology-agnostic motion codes from visual input. The framework was trained on Mobjaverse, a large-scale dataset featuring over 5,000 skeletal topologies, enabling zero-shot retargeting for diverse 3D characters. AI

IMPACT Enables animation of arbitrary 3D characters from video, potentially streamlining content creation for games and VFX.

RANK_REASON The cluster contains a research paper detailing a new method for video-to-animation retargeting.

Read on arXiv cs.CV →

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

COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Cheng-Feng Pu, Jia-Peng Zhang, Meng-Hao Guo, Yan-Pei Cao, Shi-Min Hu ·

    TopoCap: Learning Topology-Agnostic Motion Priors for Monocular Video-to-Animation

    arXiv:2606.12153v1 Announce Type: new Abstract: The explosion of generative 3D assets has created a massive demand for animation, yet current motion capture methods remain brittle, restricted to species-specific templates (e.g., SMPL) or requiring labor-intensive manual rigging. …

  2. arXiv cs.CV TIER_1 English(EN) · Shi-Min Hu ·

    TopoCap: Learning Topology-Agnostic Motion Priors for Monocular Video-to-Animation

    The explosion of generative 3D assets has created a massive demand for animation, yet current motion capture methods remain brittle, restricted to species-specific templates (e.g., SMPL) or requiring labor-intensive manual rigging. We introduce TopoCap, the first unified framewor…

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