The TransGS approach, while innovative, has several potential limitations that could be addressed to enhance its capabilities:
Limited Expression Range: The current model may struggle with extreme facial expressions that deviate significantly from the training data. To improve this, a more extensive dataset encompassing a broader range of expressions could be collected, including exaggerated and nuanced facial movements. Additionally, incorporating a more sophisticated blendshape system could allow for finer control over facial animations.
Lighting Condition Variability: Although TransGS supports HDR lighting conditions, it may not perform optimally under unconventional or dynamic lighting scenarios. Enhancing the model's robustness to various lighting conditions could involve training with a diverse set of HDR environment maps that simulate different times of day, weather conditions, and artificial lighting setups.
Real-Time Performance Constraints: While the current implementation achieves real-time rendering on mobile platforms, the complexity of the facial assets may lead to performance bottlenecks in more demanding scenarios. Optimizing the Gaussian representation further, perhaps through adaptive sampling techniques or more efficient data structures, could help maintain high frame rates even with complex animations.
Generalization to Unseen Data: The model's reliance on specific training data may limit its ability to generalize to unseen facial assets or styles. Implementing a few-shot learning approach or leveraging generative adversarial networks (GANs) could enhance the model's adaptability to new inputs.
User Interaction and Customization: Enhancing user interaction capabilities, such as allowing users to modify expressions or lighting conditions in real-time, could improve the overall experience. This could be achieved by integrating intuitive user interfaces that facilitate easy adjustments to the facial parameters.
By addressing these limitations, the TransGS approach could be significantly improved, enabling it to handle a wider range of facial expressions and lighting conditions, thus enhancing its applicability in various interactive environments.