Core Viewpoint - The article discusses the development of AnimaX, an efficient feedforward 3D animation generation framework that supports arbitrary skeletal topologies while combining the diversity of video priors with the controllability of skeletal animation [2][8]. Group 1: Limitations of Traditional Methods - Traditional 3D animation relies on skeletal binding and keyframe design, which, while providing high quality and control, requires significant human labor and time [11]. - Existing methods based on motion capture diffusion models or autoregressive models are limited to fixed skeletal topologies and primarily focus on humanoid actions, making them difficult to generalize to a wider range of character types [3][11]. - Video generation models can produce diverse dynamic sequences but often depend on high degrees of freedom in 3D deformation field optimization, leading to high computational costs and unstable results [3][11]. Group 2: AnimaX Framework - AnimaX integrates motion priors from video diffusion models with low-degree control of skeletal animation, innovatively representing 3D actions as multi-view, multi-frame 2D pose maps [5][12]. - The framework employs a video-pose joint diffusion model that can simultaneously generate RGB videos and corresponding pose sequences, achieving effective spatiotemporal alignment through shared positional encoding and modality-specific embeddings [5][12][14]. - AnimaX is capable of generating natural and coherent animation videos for various categories of 3D meshes, including humanoid characters, animals, and mechanical structures, completing the animation sequence generation in minutes while maintaining action diversity and realism [9][10]. Group 3: Performance and Comparisons - AnimaX has been quantitatively and qualitatively compared with several leading open-source models, demonstrating superior results across multiple metrics, particularly in appearance quality [18][21]. - In user preference tests, AnimaX achieved the highest preference rates across all evaluated aspects, including action-text matching, shape consistency, and overall motion quality [24]. - The model's design allows for robust transfer of motion priors from video diffusion models to skeletal-driven 3D animation synthesis, showcasing its advantages over existing methods [21][24]. Group 4: Future Prospects - The AnimaX research team suggests that the method can be extended beyond skeletal animation to scene-level dynamic modeling, potentially advancing broader 4D content generation [30]. - Future developments may involve integrating long-sequence video generation to enhance the continuity and detail fidelity of long-range animations, supporting more complex and richer 3D animation generation [30].