most citedPix2Vex: Image-to-Geometry Reconstruction using a Smooth Differentiable Renderer

40 citations · 42 across the 3 of their papers we have counts for

collaborators

6 papers

cs.GR20202 cited

Palettailor: Discriminable Colorization for Categorical Data

Kecheng Lu, Mi Feng, Xin Chen +5

We present an integrated approach for creating and assigning color palettes to different visualizations such as multi-class scatterplots, line, and bar charts. While other methods…

cs.GR2020

Procedural Urban Forestry

Till Niese, Sören Pirk, Matthias Albrecht +2

The placement of vegetation plays a central role in the realism of virtual scenes. We introduce procedural placement models (PPMs) for vegetation in urban layouts. PPMs are environ…

cs.HC2019

Semantic Concept Spaces: Guided Topic Model Refinement using Word-Embedding Projections

Mennatallah El-Assady, Rebecca Kehlbeck, Christopher Collins +2

We present a framework that allows users to incorporate the semantics of their domain knowledge for topic model refinement while remaining model-agnostic. Our approach enables user…

cs.LG2019

AlgoNet: Smooth Algorithmic Neural Networks

Felix Petersen, Christian Borgelt, Oliver Deussen

Artificial neural networks revolutionized many areas of computer science in recent years since they provide solutions to a number of previously unsolved problems. On the other hand…

cs.LG2019

Uncertainty-Aware Principal Component Analysis

Jochen Görtler, Thilo Spinner, Dirk Streeb +2

We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA)…

cs.CV201940 cited

Pix2Vex: Image-to-Geometry Reconstruction using a Smooth Differentiable Renderer

Felix Petersen, Amit H. Bermano, Oliver Deussen +1

The long-coveted task of reconstructing 3D geometry from images is still a standing problem. In this paper, we build on the power of neural networks and introduce Pix2Vex, a networ…