Mesh Quality

Mesh quality assessment focuses on developing methods to objectively measure the visual fidelity and suitability of 3D meshes, particularly those with texture maps, for various applications like animation and fluid dynamics simulations. Current research emphasizes creating large, diverse datasets of meshes with known distortions and corresponding human perception scores to benchmark objective quality metrics. These metrics are often based on neural networks, such as graph attention models, or novel algorithms that analyze both geometric and color information within the mesh. Improved mesh quality assessment is crucial for optimizing mesh compression, enhancing simulation accuracy, and generally improving the quality of 3D content across numerous fields.