ChatAnyone's underlying technical architecture
ChatAnyone employs the cutting-edge Hierarchical Motion Diffusion Model as its core technological framework, an important innovation in the field of digital person generation by the HumanAIGC team. The model transforms static image and audio inputs into coherent motion sequences through the multi-stage processing capabilities of the diffusion algorithm. For specific implementation, the model is layered to handle three key dimensions: 1) the head movement layer is responsible for generating natural head rotation; 2) the gesture movement layer simulates human upper limb body language; and 3) the expression layer ensures that facial micro-expressions are synchronized with the speech content. This layered design allows the system to process the motion parameters of different body parts in parallel, and generates more biomechanically correct motion sequences compared to traditional single-layer LSTM schemes.
In the technical demonstration, the system was able to stably output a 512×768 resolution, 30FPS video stream in an NVIDIA 4090 GPU environment, proving the engineering feasibility of the architecture. The project's GitHub page reveals that the motion diffusion model was trained using more than 1,000 hours of labeled motion data containing body language features from a variety of cultural backgrounds. While the current code is not fully open-sourced, the technical route has provided a learnable solution for the digital human field.
This answer comes from the articleChatAnyone: a tool for generating half-body digital human portrait videos from photosThe
