1 citations · 1 across the 4 of their papers we have counts for
4 papers
End-to-End Implicit Neural Representations for Classification
Alexander Gielisse, Jan van Gemert
Implicit neural representations (INRs) such as NeRF and SIREN encode a signal in neural network parameters and show excellent results for signal reconstruction. Using INRs for down…
ARC: Anchored Representation Clouds for High-Resolution INR Classification
Joost Luijmes, Alexander Gielisse, Roman Knyazhitskiy +1
Implicit neural representations (INRs) encode signals in neural network weights as a memory-efficient representation, decoupling sampling resolution from the associated resource co…
Local Attention Transformers for High-Detail Optical Flow Upsampling
Alexander Gielisse, Nergis Tömen, Jan van Gemert
Most recent works on optical flow use convex upsampling as the last step to obtain high-resolution flow. In this work, we show and discuss several issues and limitations of this cu…
Color Equivariant Convolutional Networks
Attila Lengyel, Ombretta Strafforello, Robert-Jan Bruintjes +2
Color is a crucial visual cue readily exploited by Convolutional Neural Networks (CNNs) for object recognition. However, CNNs struggle if there is data imbalance between color vari…