5 citations · 7 across the 3 of their papers we have counts for
5 papers
Discovering Latent Classes for Semi-Supervised Semantic Segmentation
Olga Zatsarynna, Johann Sawatzky, Juergen Gall
High annotation costs are a major bottleneck for the training of semantic segmentation systems. Therefore, methods working with less annotation effort are of special interest. This…
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation
Johann Sawatzky, Debayan Banerjee, Juergen Gall
Since acquiring pixel-wise annotations for training convolutional neural networks for semantic image segmentation is time-consuming, weakly supervised approaches that only require…
What Object Should I Use? - Task Driven Object Detection
Johann Sawatzky, Yaser Souri, Christian Grund +1
When humans have to solve everyday tasks, they simply pick the objects that are most suitable. While the question which object should one use for a specific task sounds trivial for…
Two Stream 3D Semantic Scene Completion
Martin Garbade, Yueh-Tung Chen, Johann Sawatzky +1
Inferring the 3D geometry and the semantic meaning of surfaces, which are occluded, is a very challenging task. Recently, a first end-to-end learning approach has been proposed tha…
Adaptive Binarization for Weakly Supervised Affordance Segmentation
Johann Sawatzky, Juergen Gall
The concept of affordance is important to understand the relevance of object parts for a certain functional interaction. Affordance types generalize across object categories and ar…