collaborators

9 papers

cs.CV2026

Flow-Corrected Shape Optimization: Taming Manifold Drift in High-Dimensional 3D Models

Emilien Seiler, Nicolas Talabot, Yingxuan You +2

Optimizing 3D shapes within the latent spaces of deep generative models is fundamental to computer assisted engineering, yet remains prone to a critical failure mode we term manifo…

cs.CV2026

End-to-End 4D Heart Mesh Recovery Across Full-Stack and Sparse Cardiac MRI

Yihong Chen, Jiancheng Yang, Deniz Sayin Mercadier +3

Reconstructing cardiac motion from CMR sequences is critical for diagnosis, prognosis, and intervention. Existing methods rely on complete CMR stacks to infer full heart motion, li…

cs.CV2026

S2MDF: A Plug-And-Play Layer for Intersection-Free Multi-Object Signed Distance Fields

Deniz Sayin Mercadier, Federico Stella, Aurel Bizeau +2

Compositional implicit surface representations model scenes as collections of objects, each encoded by a Signed Distance Field (SDF). A fundamental limitation of this approach is t…

cs.CV2026

Limited-Angle Tomography Reconstruction via Projector Guided 3D Diffusion

Zhantao Deng, Mériem Er-Rafik, Anna Sushko +2

Limited-angle electron tomography aims to reconstruct 3D shapes from 2D projections of Transmission Electron Microscopy (TEM) within a restricted range and number of tilting angles…

cs.CV2026

PhysGen: Physically Grounded 3D Shape Generation for Industrial Design

Yingxuan You, Chen Zhao, Hantao Zhang +2

Existing generative models for 3D shapes can synthesize high-fidelity and visually plausible shapes. For certain classes of shapes that have undergone an engineering design process…

cs.CV2025

PrIntMesh: Precise Intersection Surfaces for 3D Organ Mesh Reconstruction

Deniz Sayin Mercadier, Hieu Le, Yihong Chen +3

Human organs are composed of interconnected substructures whose geometry and spatial relationships constrain one another. Yet, most deep-learning approaches treat these parts indep…