1.2k citations · 2.2k across the 48 of their papers we have counts for
56 papers
Patternshop: Editing Point Patterns by Image Manipulation
Xingchang Huang, Tobias Ritschel, Hans-Peter Seidel +2
Point patterns are characterized by their density and correlation. While spatial variation of density is well-understood, analysis and synthesis of spatially-varying correlation is…
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
Navid Ansari, Alireza Javanmardi, Eyke Hüllermeier +2
Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions. It is therefore an attractive tool for engineering design proble…
Neural Field Convolutions by Repeated Differentiation
Ntumba Elie Nsampi, Adarsh Djeacoumar, Hans-Peter Seidel +2
Neural fields are evolving towards a general-purpose continuous representation for visual computing. Yet, despite their numerous appealing properties, they are hardly amenable to s…
Revisiting Image Deblurring with an Efficient ConvNet
Lingyan Ruan, Mojtaba Bemana, Hans-peter Seidel +2
Image deblurring aims to recover the latent sharp image from its blurry counterpart and has a wide range of applications in computer vision. The Convolution Neural Networks (CNNs)…
GlowGAN: Unsupervised Learning of HDR Images from LDR Images in the Wild
Chao Wang, Ana Serrano, Xingang Pan +5
Most in-the-wild images are stored in Low Dynamic Range (LDR) form, serving as a partial observation of the High Dynamic Range (HDR) visual world. Despite limited dynamic range, th…
Scalable multi-class sampling via filtered sliced optimal transport
Corentin Salaün, Iliyan Georgiev, Hans-Peter Seidel +1
We propose a multi-class point optimization formulation based on continuous Wasserstein barycenters. Our formulation is designed to handle hundreds to thousands of optimization obj…
Autoinverse: Uncertainty Aware Inversion of Neural Networks
Navid Ansari, Hans-Peter Seidel, Nima Vahidi Ferdowsi +1
Neural networks are powerful surrogates for numerous forward processes. The inversion of such surrogates is extremely valuable in science and engineering. The most important proper…
Physics Informed Neural Fields for Smoke Reconstruction with Sparse Data
Mengyu Chu, Lingjie Liu, Quan Zheng +4
High-fidelity reconstruction of fluids from sparse multiview RGB videos remains a formidable challenge due to the complexity of the underlying physics as well as complex occlusion…
Practical Saccade Prediction for Head-Mounted Displays: Towards a Comprehensive Model
Elena Arabadzhiyska, Cara Tursun, Hans-Peter Seidel +1
Eye-tracking technology is an integral component of new display devices such as virtual and augmented reality headsets. Applications of gaze information range from new interaction…
Eikonal Fields for Refractive Novel-View Synthesis
Mojtaba Bemana, Karol Myszkowski, Jeppe Revall Frisvad +2
We tackle the problem of generating novel-view images from collections of 2D images showing refractive and reflective objects. Current solutions assume opaque or transparent light…
Neural Relightable Participating Media Rendering
Quan Zheng, Gurprit Singh, Hans-Peter Seidel
Learning neural radiance fields of a scene has recently allowed realistic novel view synthesis of the scene, but they are limited to synthesize images under the original fixed ligh…
Learning a self-supervised tone mapping operator via feature contrast masking loss
Chao Wang, Bin Chen, Hans-Peter Seidel +2
High Dynamic Range (HDR) content is becoming ubiquitous due to the rapid development of capture technologies. Nevertheless, the dynamic range of common display devices is still lim…
Mixed Integer Neural Inverse Design
Navid Ansari, Hans-Peter Seidel, Vahid Babaei
In computational design and fabrication, neural networks are becoming important surrogates for bulky forward simulations. A long-standing, intertwined question is that of inverse d…
Egocentric Videoconferencing
Mohamed Elgharib, Mohit Mendiratta, Justus Thies +5
We introduce a method for egocentric videoconferencing that enables hands-free video calls, for instance by people wearing smart glasses or other mixed-reality devices. Videoconfer…
Self-supervised Outdoor Scene Relighting
Ye Yu, Abhimitra Meka, Mohamed Elgharib +3
Outdoor scene relighting is a challenging problem that requires good understanding of the scene geometry, illumination and albedo. Current techniques are completely supervised, req…
A Variational Loop Shrinking Analogy for Handle and Tunnel Detection and Reeb Graph Construction on Surfaces
Alexander Weinrauch, Hans-Peter Seidel, Daniel Mlakar +2
The humble loop shrinking property played a central role in the inception of modern topology but it has been eclipsed by more abstract algebraic formalism. This is particularly tru…
Differentiable Event Stream Simulator for Non-Rigid 3D Tracking
Jalees Nehvi, Vladislav Golyanik, Franziska Mueller +3
This paper introduces the first differentiable simulator of event streams, i.e., streams of asynchronous brightness change signals recorded by event cameras. Our differentiable sim…
PhotoApp: Photorealistic Appearance Editing of Head Portraits
Mallikarjun B R, Ayush Tewari, Abdallah Dib +8
Photorealistic editing of portraits is a challenging task as humans are very sensitive to inconsistencies in faces. We present an approach for high-quality intuitive editing of the…
Learning Speech-driven 3D Conversational Gestures from Video
Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta +5
We propose the first approach to automatically and jointly synthesize both the synchronous 3D conversational body and hand gestures, as well as 3D face and head animations, of a vi…
High-Fidelity Neural Human Motion Transfer from Monocular Video
Moritz Kappel, Vladislav Golyanik, Mohamed Elgharib +5
Video-based human motion transfer creates video animations of humans following a source motion. Current methods show remarkable results for tightly-clad subjects. However, the lack…
HDR Denoising and Deblurring by Learning Spatio-temporal Distortion Models
Uğur Çoğalan, Mojtaba Bemana, Karol Myszkowski +2
We seek to reconstruct sharp and noise-free high-dynamic range (HDR) video from a dual-exposure sensor that records different low-dynamic range (LDR) information in different pixel…
EventHands: Real-Time Neural 3D Hand Pose Estimation from an Event Stream
Viktor Rudnev, Vladislav Golyanik, Jiayi Wang +4
3D hand pose estimation from monocular videos is a long-standing and challenging problem, which is now seeing a strong upturn. In this work, we address it for the first time using…
i3DMM: Deep Implicit 3D Morphable Model of Human Heads
Tarun Yenamandra, Ayush Tewari, Florian Bernard +4
We present the first deep implicit 3D morphable model (i3DMM) of full heads. Unlike earlier morphable face models it not only captures identity-specific geometry, texture, and expr…
Learning Complete 3D Morphable Face Models from Images and Videos
Mallikarjun B R, Ayush Tewari, Hans-Peter Seidel +2
Most 3D face reconstruction methods rely on 3D morphable models, which disentangle the space of facial deformations into identity geometry, expressions and skin reflectance. These…