75 citations · 84 across the 5 of their papers we have counts for
6 papers
Improved Robustness from Biologically Inspired Sparse Contrast Representations
Lorena Stracke, Lia Nimmermann, Shashank Agnihotri +3
Deep neural networks surpass humans on many vision benchmarks, yet remain far less robust to distribution shifts such as illumination and weather changes. Existing approaches addre…
Robust Semantic Segmentation with Superpixel-Mix
Gianni Franchi, Nacim Belkhir, Mai Lan Ha +4
Along with predictive performance and runtime speed, reliability is a key requirement for real-world semantic segmentation. Reliability encompasses robustness, predictive uncertain…
Learning a Discriminant Latent Space with Neural Discriminant Analysis
Mai Lan Ha, Gianni Franchi, Emanuel Aldea +1
Discriminative features play an important role in image and object classification and also in other fields of research such as semi-supervised learning, fine-grained classification…
Deep Ranking with Adaptive Margin Triplet Loss
Mai Lan Ha, Volker Blanz
We propose a simple modification from a fixed margin triplet loss to an adaptive margin triplet loss. While the original triplet loss is used widely in classification problems such…
3D Morphable Face Models -- Past, Present and Future
Bernhard Egger, William A. P. Smith, Ayush Tewari +10
In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, name…
Deep Convolutional Neural Networks in the Face of Caricature: Identity and Image Revealed
Matthew Q. Hill, Connor J. Parde, Carlos D. Castillo +5
Real-world face recognition requires an ability to perceive the unique features of an individual face across multiple, variable images. The primate visual system solves the problem…