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20202026
most citedGeometric implicit neural representations for signed distance functions

10 citations · 10 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2025★ 10 cited

Geometric implicit neural representations for signed distance functions

Luiz Schirmer, Tiago Novello, Vinícius da Silva +5

\textit{Implicit neural representations} (INRs) have emerged as a promising framework for representing signals in low-dimensional spaces. This survey reviews the existing literatur…

cs.CV2025

FLOWING: Implicit Neural Flows for Structure-Preserving Morphing

Arthur Bizzi, Matias Grynberg, Vitor Matias +7

Morphing is a long-standing problem in vision and computer graphics, requiring a time-dependent warping for feature alignment and a blending for smooth interpolation. Recently, mul…

cs.CV2025

VOIDFace: A Privacy-Preserving Multi-Network Face Recognition With Enhanced Security

Ajnas Muhammed, Iurri Medvedev, Nuno Gonçalves

Advancement of machine learning techniques, combined with the availability of large-scale datasets, has significantly improved the accuracy and efficiency of facial recognition. Mo…

cs.CV2025

Second Competition on Presentation Attack Detection on ID Card

Juan E. Tapia, Mario Nieto, Juan M. Espin +30

This work summarises and reports the results of the second Presentation Attack Detection competition on ID cards. This new version includes new elements compared to the previous on…

cs.CL2025

AdaSplash: Adaptive Sparse Flash Attention

Nuno Gonçalves, Marcos Treviso, André F. T. Martins

The computational cost of softmax-based attention in transformers limits their applicability to long-context tasks. Adaptive sparsity, of which -entmax attention is an example,…