1 code implementation • NeurIPS 2023 • Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
Recently, it was shown that the reconstruction of pre-trained self-supervised features leads to object-centric representations on unconstrained real-world image datasets.
3 code implementations • 29 Sep 2022 • Maximilian Seitzer, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel, Tong He, Zheng Zhang, Bernhard Schölkopf, Thomas Brox, Francesco Locatello
Humans naturally decompose their environment into entities at the appropriate level of abstraction to act in the world.
1 code implementation • 11 Jul 2022 • Andrii Zadaianchuk, Matthaeus Kleindessner, Yi Zhu, Francesco Locatello, Thomas Brox
In this paper, we show that recent advances in self-supervised feature learning enable unsupervised object discovery and semantic segmentation with a performance that matches the state of the field on supervised semantic segmentation 10 years ago.
no code implementations • 9 Sep 2021 • Andrii Zadaianchuk, Georg Martius, Fanny Yang
We propose a novel self-supervised agent that estimates relations between environment components and uses them to independently control different parts of the environment state.
1 code implementation • ICLR 2021 • Andrii Zadaianchuk, Maximilian Seitzer, Georg Martius
We show that the structure in the representations in combination with goal-conditioned attention policies helps the autonomous agent to discover and learn useful skills.