61 citations · 108 across the 14 of their papers we have counts for
10 papers · 1 filter
High Quality Monocular Depth Estimation via Transfer Learning
Ibraheem Alhashim, Peter Wonka
Accurate depth estimation from images is a fundamental task in many applications including scene understanding and reconstruction. Existing solutions for depth estimation often pro…
Latent Filter Scaling for Multimodal Unsupervised Image-to-Image Translation
Yazeed Alharbi, Neil Smith, Peter Wonka
In multimodal unsupervised image-to-image translation tasks, the goal is to translate an image from the source domain to many images in the target domain. We present a simple metho…
DuLa-Net: A Dual-Projection Network for Estimating Room Layouts from a Single RGB Panorama
Shang-Ta Yang, Fu-En Wang, Chi-Han Peng +3
We present a deep learning framework, called DuLa-Net, to predict Manhattan-world 3D room layouts from a single RGB panorama. To achieve better prediction accuracy, our method leve…
How does Lipschitz Regularization Influence GAN Training?
Yipeng Qin, Niloy Mitra, Peter Wonka
Despite the success of Lipschitz regularization in stabilizing GAN training, the exact reason of its effectiveness remains poorly understood. The direct effect of -Lipschitz reg…
FrankenGAN: Guided Detail Synthesis for Building Mass-Models Using Style-Synchonized GANs
Tom Kelly, Paul Guerrero, Anthony Steed +2
Coarse building mass models are now routinely generated at scales ranging from individual buildings through to whole cities. For example, they can be abstracted from raw measuremen…
Continuous and Orientation-preserving Correspondences via Functional Maps
Jing Ren, Adrien Poulenard, Peter Wonka +1
We propose a method for efficiently computing orientation-preserving and approximately continuous correspondences between non-rigid shapes, using the functional maps framework. We…