5 papers
Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues
Hesam Araghi, Jan van Gemert, Nergis Tomen
Event cameras capture intensity changes asynchronously with high temporal resolution, requiring novel preprocessing methods for downstream tasks. Unlike static intensity snapshots,…
Data-Efficient Challenges in Visual Inductive Priors: A Retrospective
Robert-Jan Bruintjes, Attila Lengyel, Osman Semih Kayhan +4
Deep Learning requires large amounts of data to train models that work well. In data-deficient settings, performance can be degraded. We investigate which Deep Learning methods ben…
Making Every Event Count: Balancing Data Efficiency and Accuracy in Event Camera Subsampling
Hesam Araghi, Jan van Gemert, Nergis Tomen
Event cameras offer high temporal resolution and power efficiency, making them well-suited for edge AI applications. However, their high event rates present challenges for data tra…
Pushing the boundaries of event subsampling in event-based video classification using CNNs
Hesam Araghi, Jan van Gemert, Nergis Tomen
Event cameras offer low-power visual sensing capabilities ideal for edge-device applications. However, their high event rate, driven by high temporal details, can be restrictive in…
VIPriors 4: Visual Inductive Priors for Data-Efficient Deep Learning Challenges
Robert-Jan Bruintjes, Attila Lengyel, Marcos Baptista Rios +4
The fourth edition of the "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" workshop features two data-impaired challenges. These challenges address the problem…