1 citations · 2 across the 2 of their papers we have counts for
4 papers
Domain Generalization for Semantic Segmentation: A Survey
Manuel Schwonberg, Hanno Gottschalk
The generalization of deep neural networks to unknown domains is a major challenge despite their tremendous progress in recent years. For this reason, the dynamic area of domain ge…
A Study on Unsupervised Domain Adaptation for Semantic Segmentation in the Era of Vision-Language Models
Manuel Schwonberg, Claus Werner, Hanno Gottschalk +1
Despite the recent progress in deep learning based computer vision, domain shifts are still one of the major challenges. Semantic segmentation for autonomous driving faces a wide r…
Generalization by Adaptation: Diffusion-Based Domain Extension for Domain-Generalized Semantic Segmentation
Joshua Niemeijer, Manuel Schwonberg, Jan-Aike Termöhlen +2
When models, e.g., for semantic segmentation, are applied to images that are vastly different from training data, the performance will drop significantly. Domain adaptation methods…
Strong but simple: A Baseline for Domain Generalized Dense Perception by CLIP-based Transfer Learning
Christoph Hümmer, Manuel Schwonberg, Liangwei Zhou +3
Domain generalization (DG) remains a significant challenge for perception based on deep neural networks (DNNs), where domain shifts occur due to synthetic data, lighting, weather,…