collaborators

43 papers

cs.LG2026

Forgetting, plasticity, and co-observation: a third facet of continual learning

Timm Hess, Abhishek Jha, Gido M. van de Ven +1

Efficient continual learning remains a fundamental challenge for deep neural networks. While catastrophic forgetting and loss of plasticity are widely considered the primary obstac…

cs.CV2026

Learning visual representations for compositional analysis of artworks and photographs

Fatemeh Behrad, Tinne Tuytelaars, Johan Wagemans

Composition, the deliberate arrangement of visual elements, is central to how meaning, emotion, and aesthetic quality are conveyed in artwork, yet it remains among the least formal…

cs.RO2026

DemoBridge: A Simulation-in-the-Loop Toolkit for Single-View Human Demonstration Retargeting

Zehao Wang, Fabien Despinoy, Sergey Zakharov +2

We present DemoBridge, an toolkit that turns a single-view RGB stereo recording of a human hand demonstration into an executable, physics-validated robot-arm trajectory. Retargetin…

cs.CV2026

Lifelong Representations: A Survey on Continual Self-Supervised Learning for Vision Models

Sergi Masip, Alicja Dobrzeniecka, Jonathan Swinnen +4

Traditionally, continual learning has assumed access to labeled data, yet many real-world applications -- such as lifelong robotics -- require models to adapt continuously from unl…

eess.SP2026

Eccentricity Confound in EEG-based Visual Attention Decoding from Gaze-Fixated Neural Tracking of Motion in Natural Videos

Yuanyuan Yao, Celina Salamanca Gonzalez, Simon Geirnaert +3

Objective. Decoding visual attention from brain signals during naturalistic video viewing has emerged as a new direction in brain-computer interface research. Current methods assum…

cs.LG2026

Adversarial Dependence Minimization

Pierre-François De Plaen, Tinne Tuytelaars, Marc Proesmans +1

Minimally redundant representations are typically learned by minimizing feature covariance. However, covariance-based methods fail to eliminate all dependencies/redundancies, as li…