KaiNinja extends native 3D generators to produce part-level assets by using a dual-volume representation, improving generation speed and quality without segmentation. It achieves better whole-object fidelity and part-level metrics compared to existing methods.
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This method enables faster and more accurate part-level 3D generation without relying on segmentation networks, improving both whole-object and part-level performance.
The paper introduces Vidu S2, a system with two components: Vidu S2-Avatar for real-time interactive digital characters and Vidu S2-Editing for real-time video editing. It also explores real-time spatial video generation for both components. Compared to its predecessor, Vidu S2-Avatar offers improved real-time 720p video generation, dynamic reference updates, and enhanced instruction following. Vidu S2-Editing enables real-time video stream editing with features like style rendering and background replacement.
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