OptimusMesh: Compact Autoregressive Mesh Generation from Point Clouds via Sparse Latent Pivots
This study addresses the tendency of existing point cloud-to-3D mesh generation methods to produce overly dense meshes with high post-processing costs. To overcome this limitation, this work proposes OptimusMesh, a framework that compresses 2,048 input points into 16 sparse latent pivots, substantially shortening the conditioning sequence. Furthermore, it introduces a two-stage autoregressive architecture that jointly predicts vertices and faces, enabling the direct generation of compact triangular meshes. Compared with state-of-the-art approaches, the proposed method reduces the number of generated mesh faces by 25.7%–94.1%, significantly improving generation efficiency while maintaining competitive geometric fidelity and distribution quality.