activity
20232026
most citedOpenMask3D: Open-Vocabulary 3D Instance Segmentation

29 citations · 33 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

SuperFlex: Deformable Superquadrics for Point Cloud Decomposition

Gabriel Tavernini, Elisabetta Fedele, Tiago Novello +3

Superquadrics have proven to provide a compact, geometrically meaningful representation for 3D objects. However, existing methods suffer from limited reconstruction accuracy, are r…

cs.CV2025

SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling

Elisabetta Fedele, Francis Engelmann, Ian Huang +3

Generative methods for 3D assets have recently achieved remarkable progress, yet providing intuitive and precise control over the object geometry remains a key challenge. Existing…

cs.CV2025

SuperDec: 3D Scene Decomposition with Superquadric Primitives

Elisabetta Fedele, Boyang Sun, Leonidas Guibas +2

We present SuperDec, an approach for creating compact 3D scene representations via decomposition into superquadric primitives. While most recent works leverage geometric primitives…

cs.CV2024★ 1 cited

OpenSUN3D: 1st Workshop Challenge on Open-Vocabulary 3D Scene Understanding

Francis Engelmann, Ayca Takmaz, Jonas Schult +25

This report provides an overview of the challenge hosted at the OpenSUN3D Workshop on Open-Vocabulary 3D Scene Understanding held in conjunction with ICCV 2023. The goal of this wo…

cs.CV2023★ 3 cited

FABRIC: Personalizing Diffusion Models with Iterative Feedback

Dimitri von Rütte, Elisabetta Fedele, Jonathan Thomm +1

In an era where visual content generation is increasingly driven by machine learning, the integration of human feedback into generative models presents significant opportunities fo…

cs.CV2023★ 29 cited

OpenMask3D: Open-Vocabulary 3D Instance Segmentation

Ayça Takmaz, Elisabetta Fedele, Robert W. Sumner +3

We introduce the task of open-vocabulary 3D instance segmentation. Current approaches for 3D instance segmentation can typically only recognize object categories from a pre-defined…