Your AI-generated 3D model is noisy typically due to three main issues: insufficient high-quality training data, misconfigured model parameters (e.g., an overly high learning rate), or low-resolution input during inference.
Insufficient training data means the model can’t learn clear 3D patterns, so it guesses—resulting in noisy outputs. Misconfigured parameters (like too high a learning rate) make predictions unstable and inconsistent. Low-resolution inputs force the model to fill gaps with random, noisy details.
To fix this, try improving your training data’s quality/diversity, adjusting parameters (lower learning rate, add regularization), or using higher-resolution inputs for inference.