9 papers
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…
High Resolution UDF Meshing via Iterative Networks
Federico Stella, Nicolas Talabot, Hieu Le +1
Unsigned Distance Fields (UDFs) are a natural implicit representation for open surfaces but, unlike Signed Distance Fields (SDFs), are challenging to triangulate into explicit mesh…
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…
Gradient Distance Function
Hieu Le, Federico Stella, Benoit Guillard +1
Unsigned Distance Functions (UDFs) can be used to represent non-watertight surfaces in a deep learning framework. However, UDFs tend to be brittle and difficult to learn, in part b…
Counting Stacked Objects
Corentin Dumery, Noa Etté, Aoxiang Fan +4
Visual object counting is a fundamental computer vision task underpinning numerous real-world applications, from cell counting in biomedicine to traffic and wildlife monitoring. Ho…
High-Fidelity and Generalizable Neural Surface Reconstruction with Sparse Feature Volumes
Aoxiang Fan, Corentin Dumery, Nicolas Talabot +2
Generalizable neural surface reconstruction has become a compelling technique to reconstruct from few images without per-scene optimization, where dense 3D feature volume has prove…