2 papers
cs.CV2021
Essentials for Class Incremental Learning
Sudhanshu Mittal, Silvio Galesso, Thomas Brox
Contemporary neural networks are limited in their ability to learn from evolving streams of training data. When trained sequentially on new or evolving tasks, their accuracy drops…
cs.CV2018
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
Eddy Ilg, Özgün Çiçek, Silvio Galesso +4
Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative met…