Smoothing Continual Segmentation Oscillations with Latent Domain PPCA Decoder

Marie-Ange Boum, Pierre Fournier, Dawa Derksen, Stéphane Herbin

Keywords: domain incremental learning, semantic segmentation, foundation models, dinov2, ppca

Abstract: We study Domain Incremental Learning for the semantic segmentation of Earth Observation images. We demonstrate that controlling the oscillation of performance when a new domain arrives is more critical than controlling catastrophic forgetting. We propose an exemplar-free architecture that combines a large pre-trained network well adapted to dense image processing (DINOv2) and a generative decoder head based on Probabilitic Principal Component Analysis (PPCA). We validate our approach on the FLAIR\#1 high-resolution dataset, which is structured as a sequence of domains.

Submission Number: 35