{"ID":2882842,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.09858","arxiv_id":"2508.09858","title":"HumanGenesis: Agent-Based Geometric and Generative Modeling for Synthetic Human Dynamics","abstract":"\\textbf{Synthetic human dynamics} aims to generate photorealistic videos of human subjects performing expressive, intention-driven motions. However, current approaches face two core challenges: (1) \\emph{geometric inconsistency} and \\emph{coarse reconstruction}, due to limited 3D modeling and detail preservation; and (2) \\emph{motion generalization limitations} and \\emph{scene inharmonization}, stemming from weak generative capabilities. To address these, we present \\textbf{HumanGenesis}, a framework that integrates geometric and generative modeling through four collaborative agents: (1) \\textbf{Reconstructor} builds 3D-consistent human-scene representations from monocular video using 3D Gaussian Splatting and deformation decomposition. (2) \\textbf{Critique Agent} enhances reconstruction fidelity by identifying and refining poor regions via multi-round MLLM-based reflection. (3) \\textbf{Pose Guider} enables motion generalization by generating expressive pose sequences using time-aware parametric encoders. (4) \\textbf{Video Harmonizer} synthesizes photorealistic, coherent video via a hybrid rendering pipeline with diffusion, refining the Reconstructor through a Back-to-4D feedback loop. HumanGenesis achieves state-of-the-art performance on tasks including text-guided synthesis, video reenactment, and novel-pose generalization, significantly improving expressiveness, geometric fidelity, and scene integration.","short_abstract":"\\textbf{Synthetic human dynamics} aims to generate photorealistic videos of human subjects performing expressive, intention-driven motions. However, current approaches face two core challenges: (1) \\emph{geometric inconsistency} and \\emph{coarse reconstruction}, due to limited 3D modeling and detail preservation; and (...","url_abs":"https://arxiv.org/abs/2508.09858","url_pdf":"https://arxiv.org/pdf/2508.09858v1","authors":"[\"Weiqi Li\",\"Zehao Zhang\",\"Liang Lin\",\"Guangrun Wang\"]","published":"2025-08-13T14:50:19Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[\"Diffusion Model\",\"Large Language Model\"]","has_code":false}