284 citations · 405 across the 19 of their papers we have counts for
5 papers · 1 filter
Learning Generative Models of Textured 3D Meshes from Real-World Images
Dario Pavllo, Jonas Kohler, Thomas Hofmann +1
Recent advances in differentiable rendering have sparked an interest in learning generative models of textured 3D meshes from image collections. These models natively disentangle p…
Convolutional Generation of Textured 3D Meshes
Dario Pavllo, Graham Spinks, Thomas Hofmann +2
While recent generative models for 2D images achieve impressive visual results, they clearly lack the ability to perform 3D reasoning. This heavily restricts the degree of control…
Controlling Style and Semantics in Weakly-Supervised Image Generation
Dario Pavllo, Aurelien Lucchi, Thomas Hofmann
We propose a weakly-supervised approach for conditional image generation of complex scenes where a user has fine control over objects appearing in the scene. We exploit sparse sema…
Topological Map Extraction from Overhead Images
Zuoyue Li, Jan Dirk Wegner, Aurélien Lucchi
We propose a new approach, named PolyMapper, to circumvent the conventional pixel-wise segmentation of (aerial) images and predict objects in a vector representation directly. Poly…
Learning Aerial Image Segmentation from Online Maps
Pascal Kaiser, Jan Dirk Wegner, Aurelien Lucchi +3
This study deals with semantic segmentation of high-resolution (aerial) images where a semantic class label is assigned to each pixel via supervised classification as a basis for a…