6 citations · 8 across the 10 of their papers we have counts for
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cs.CV2019
Casting Geometric Constraints in Semantic Segmentation as Semi-Supervised Learning
Sinisa Stekovic, Friedrich Fraundorfer, Vincent Lepetit
We propose a simple yet effective method to learn to segment new indoor scenes from video frames: State-of-the-art methods trained on one dataset, even as large as the SUNRGB-D dat…
cs.CV2019★ 1 cited
S4-Net: Geometry-Consistent Semi-Supervised Semantic Segmentation
Sinisa Stekovic, Friedrich Fraundorfer, Vincent Lepetit
We show that it is possible to learn semantic segmentation from very limited amounts of manual annotations, by enforcing geometric 3D constraints between multiple views. More exact…