[ECCV 2026] SuperFlex: Deformable Superquadrics for Point Cloud Decomposition

Project page: https://superflex3d.github.io Authors: Gabriel Tavernini, Elisabetta Fedele, Tiago Novello, Leonidas Guibas, Marc Pollefeys, Francis Engelmann. Abstract: While recent advances like SuperDec have revitalized superquadrics for compact 3D scene understanding, they remain limited by rigid geometric constraints and lack robustness to partial observations. We present SuperFlex, an enhanced framework expanding the expressive power and applicability of superquadric decompositions. First, we include bending and tapering parameters, enabling high-fidelity representation of complex geometries. Second, a novel loss formulation and optimization scheme refines initial decompositions, significantly improving accuracy. These high-fidelity primitives enable training a robust model for direct prediction from noisy, partial real-world point clouds, a task previously infeasible for methods requiring full point clouds.