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cs.CV2025
The Joint Gromov Wasserstein Objective for Multiple Object Matching
Aryan Tajmir Riahi, Khanh Dao Duc
The Gromov-Wasserstein (GW) distance serves as a powerful tool for matching objects in metric spaces. However, its traditional formulation is constrained to pairwise matching betwe…
cs.CV2025
CryoSAMU: Enhancing 3D Cryo-EM Density Maps of Protein Structures at Intermediate Resolution with Structure-Aware Multimodal U-Nets
Chenwei Zhang, Khanh Dao Duc
Enhancing cryogenic electron microscopy (cryo-EM) 3D density maps at intermediate resolution (4-8 Å) is crucial in protein structure determination. Recent advances in deep learning…
cs.CV2022
Defining an action of SO(d)-rotations on images generated by projections of d-dimensional objects: Applications to pose inference with Geometric VAEs
Nicolas Legendre, Khanh Dao Duc, Nina Miolane
Recent advances in variational autoencoders (VAEs) have enabled learning latent manifolds as compact Lie groups, such as . Since this approach assumes that data lies on a su…