Static Mesh

Static mesh processing focuses on efficiently representing and manipulating 3D shapes with texture, crucial for applications like animation and medical imaging. Current research emphasizes developing robust quality assessment metrics for these meshes, often employing model-based approaches that incorporate both geometric and color information, and exploring novel neural network architectures like graph convolutional networks (GCNs) for tasks such as mesh refinement and shape understanding. The development of accurate quality metrics and improved processing techniques is vital for advancing mesh compression, enhancing rendering quality, and improving the efficiency of various 3D applications.