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Related Experiment Video

Updated: Apr 8, 2026

Measuring Connectivity in the Primary Visual Pathway in Human Albinism Using Diffusion Tensor Imaging and Tractography
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Motion2VecSets: Non-Rigid Shape Reconstruction and Tracking With 4D Latent Set Diffusion.

Jiapeng Tang, Wei Cao, Biao Zhang

    IEEE Transactions on Pattern Analysis and Machine Intelligence
    |April 6, 2026
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    Summary
    This summary is machine-generated.

    Motion2VecSets, a novel 4D diffusion model, generates dynamic surface meshes from ambiguous data. It enhances non-rigid object reconstruction and motion capture using latent sets for improved generalization.

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    Area of Science:

    • Computer Vision
    • Machine Learning
    • 3D Computer Graphics

    Background:

    • Neural fields excel at non-rigid object modeling but struggle with ambiguous inputs.
    • Deterministic feed-forward models fail with noisy, partial, or sparse observations.

    Purpose of the Study:

    • Introduce a 4D diffusion model for dynamic surface mesh generation from diverse, imperfect observations.
    • Address the one-to-many mapping problem in non-rigid object reconstruction.

    Main Methods:

    • Utilize a diffusion model for iterative denoising of compressed latent representations.
    • Employ latent sets to capture local shape and deformation patterns in 4D dynamics.
    • Incorporate interleaved spatial-temporal attention for computational efficiency.

    Main Results:

    • Achieve more plausible and diverse reconstructions under ambiguous conditions.
    • Demonstrate accurate non-linear motion capture and improved generalization to unseen motions.
    • Outperform prior methods in reconstructing and tracking non-rigid deformations from imperfect data.

    Conclusions:

    • Motion2VecSets effectively reconstructs and tracks dynamic non-rigid objects from challenging, real-world observations.
    • The latent set representation significantly enhances generalization for 4D shape and motion modeling.
    • This diffusion-based approach offers a robust solution for dynamic surface mesh generation.