no code implementations • 25 Mar 2022 • Wenbin He, William Surmeier, Arvind Kumar Shekar, Liang Gou, Liu Ren
In this work, we propose a self-supervised pixel representation learning method for semantic segmentation by using visual concepts (i. e., groups of pixels with semantic meanings, such as parts, objects, and scenes) extracted from images.
no code implementations • 3 Jan 2022 • Arvind Kumar Shekar, Laureen Lake, Liang Gou, Liu Ren
It is on this space we estimate the novelty of the test samples.
no code implementations • 27 Sep 2020 • Liang Gou, Lincan Zou, Nanxiang Li, Michael Hofmann, Arvind Kumar Shekar, Axel Wendt, Liu Ren
In this work, we propose a visual analytics system, VATLD, equipped with a disentangled representation learning and semantic adversarial learning, to assess, understand, and improve the accuracy and robustness of traffic light detectors in autonomous driving applications.
no code implementations • 16 Apr 2018 • Arvind Kumar Shekar, Cláudio Rebelo de Sá, Hugo Ferreira, Carlos Soares
Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges.