38 citations · 81 across the 10 of their papers we have counts for
11 papers
Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation
Achref Jaziri, Martin Mundt, Andres Fernandez Rodriguez +1
Identification of cracks is essential to assess the structural integrity of concrete infrastructure. However, robust crack segmentation remains a challenging task for computer visi…
A Procedural World Generation Framework for Systematic Evaluation of Continual Learning
Timm Hess, Martin Mundt, Iuliia Pliushch +1
Several families of continual learning techniques have been proposed to alleviate catastrophic interference in deep neural network training on non-stationary data. However, a compr…
When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics
Iuliia Pliushch, Martin Mundt, Nicolas Lupp +1
Although a plethora of architectural variants for deep classification has been introduced over time, recent works have found empirical evidence towards similarities in their traini…
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
Martin Mundt, Yongwon Hong, Iuliia Pliushch +1
Current deep learning methods are regarded as favorable if they empirically perform well on dedicated test sets. This mentality is seamlessly reflected in the resurfacing area of c…
Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?
Martin Mundt, Iuliia Pliushch, Sagnik Majumder +1
We present an analysis of predictive uncertainty based out-of-distribution detection for different approaches to estimate various models' epistemic uncertainty and contrast it with…
Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
Martin Mundt, Iuliia Pliushch, Sagnik Majumder +2
Modern deep neural networks are well known to be brittle in the face of unknown data instances and recognition of the latter remains a challenge. Although it is inevitable for cont…