30 citations · 140 across the 23 of their papers we have counts for
4 papers · 1 filter
Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness
Boqian Wu, Qiao Xiao, Shunxin Wang +5
It is generally perceived that Dynamic Sparse Training opens the door to a new era of scalability and efficiency for artificial neural networks at, perhaps, some costs in accuracy…
PushPull-Net: Inhibition-driven ResNet robust to image corruptions
Guru Swaroop Bennabhaktula, Enrique Alegre, Nicola Strisciuglio +1
We introduce a novel computational unit, termed PushPull-Conv, in the first layer of a ResNet architecture, inspired by the anti-phase inhibition phenomenon observed in the primary…
Fourier-basis Functions to Bridge Augmentation Gap: Rethinking Frequency Augmentation in Image Classification
Puru Vaish, Shunxin Wang, Nicola Strisciuglio
Computer vision models normally witness degraded performance when deployed in real-world scenarios, due to unexpected changes in inputs that were not accounted for during training.…
Regressing Transformers for Data-efficient Visual Place Recognition
María Leyva-Vallina, Nicola Strisciuglio, Nicolai Petkov
Visual place recognition is a critical task in computer vision, especially for localization and navigation systems. Existing methods often rely on contrastive learning: image descr…