3 papers
cs.CV2026
Improving Generative Adversarial Networks with Self-Distillation
Antoni Nowinowski, Krzysztof Krawiec
In modern GANs, maintaining an Exponential Moving Average (EMA) of the generator's weights is a standard practice, as such an averaged model consistently outperforms the actively t…
cs.CV2025
Generative Learning of Differentiable Object Models for Compositional Interpretation of Complex Scenes
Antoni Nowinowski, Krzysztof Krawiec
This study builds on the architecture of the Disentangler of Visual Priors (DVP), a type of autoencoder that learns to interpret scenes by decomposing the perceived objects into in…
cs.CV2024
Disentangling Visual Priors: Unsupervised Learning of Scene Interpretations with Compositional Autoencoder
Krzysztof Krawiec, Antoni Nowinowski
Contemporary deep learning architectures lack principled means for capturing and handling fundamental visual concepts, like objects, shapes, geometric transforms, and other higher-…