After skimming here is my (imperfect) summary. Comments encouraged! Technique: "Neural Geometric LOD (level of detail)" Summary: This technique provides a mac

After skimming here is my (imperfect) summary. Comments encouraged! Technique: "Neural Geometric LOD (level of detail)" Summary: This technique provides a machine-learning approach to give more efficient representation for 3D surfaces at interactive rates. Related Work: "Our work is most related to prior research on mesh simplification for level of detail (LOD), 3D neural shape representations, and implicit neural rendering." Method: "Our goal is to design a representation which reconstructs detailed geometry and enables continuous level of detail, all whilst being able to render at interactive rates." Experiments: "Across all [tested] datasets [(ShapeNet, Thingi10K, TurboSquid, Shadertoy)] and metrics, we achieve state-of-the-art results" relative to DeepSDF, Fourier Feature Networks, SIREN, and Neural Implicits (NI). Generalization: "surface extraction mechanism can generalize to multiple shapes, even from being trained on a single shape."