25 citations · 25 across the 1 of their papers we have counts for
2 papers
cs.CV2021★ 25 cited
Domain Adaptation for Semantic Segmentation via Patch-Wise Contrastive Learning
Weizhe Liu, David Ferstl, Samuel Schulter +3
We introduce a novel approach to unsupervised and semi-supervised domain adaptation for semantic segmentation. Unlike many earlier methods that rely on adversarial learning for fea…
cs.CV2021
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank
Inigo Alonso, Alberto Sabater, David Ferstl +2
This work presents a novel approach for semi-supervised semantic segmentation. The key element of this approach is our contrastive learning module that enforces the segmentation ne…