40 citations · 63 across the 9 of their papers we have counts for
4 papers · 1 filter
GenDR: A Generalized Differentiable Renderer
Felix Petersen, Bastian Goldluecke, Christian Borgelt +1
In this work, we present and study a generalized family of differentiable renderers. We discuss from scratch which components are necessary for differentiable rendering and formali…
Style Agnostic 3D Reconstruction via Adversarial Style Transfer
Felix Petersen, Bastian Goldluecke, Oliver Deussen +1
Reconstructing the 3D geometry of an object from an image is a major challenge in computer vision. Recently introduced differentiable renderers can be leveraged to learn the 3D geo…
Shape-driven Coordinate Ordering for Star Glyph Sets via Reinforcement Learning
Ruizhen Hu, Bin Chen, Juzhan Xu +3
We present a neural optimization model trained with reinforcement learning to solve the coordinate ordering problem for sets of star glyphs. Given a set of star glyphs associated t…
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…