Towards Better Morphed Face Images Without Ghosting Artifacts
We propose a method for automatic prevention of ghosting artifacts based on a pixel-wise alignment during morph generation. We evaluate our proposed method on state-of-the-art detectors and show that our morphs are harder to detect, particularly,...
Generative Texture Super-Resolution via Differential Rendering
We propose a generative deep learning network for texture map super-resolution using a differentiable renderer and calibrated reference images. Combining a super-resolution generative adversarial network (GAN) with differentiable rendering, we...
Multi-View Inversion for 3D-aware Generative Adversarial Networks
Our method builds on existing state-of-the-art 3D GAN inversion techniques to allow for consistent and simultaneous inversion of multiple views of the same subject. We employ a multi-latent extension to handle inconsistencies present in dynamic...
Animating NeRFs from Texture Space: A Framework for Pose-Dependent Rendering of Human Performances
We introduce a novel NeRF-based framework for pose-dependent rendering of human performances where the radiance field is warped around an SMPL body mesh, thereby creating a new surface-aligned representation. Our representation can be animated...
Efficient and Accurate Hyperspectral Image Demosaicing with Neural Network Architectures
This study investigates the effectiveness of neural network architectures in hyperspectral image demosaicing. We introduce a range of network models and modifications, and compare them with classical interpolation methods and existing reference...
Insights into the inner workings of transformer models for protein function prediction
We explored how explainable artificial intelligence (XAI) can help to shed light into the inner workings of neural networks for protein function prediction, by extending the widely used XAI method of integrated gradients such that latent...
Semantic Communication for Edge Intelligence: Theoretical Foundations and Implications on Protocols
Recent attention to semantic communication, driven by task-oriented solutions, aims to optimize resource use. Despite perceived efficiency gains, few practical implementations exist. This paper revisits theoretical foundations, emphasizing...
Towards an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets
We present iV2V and iV2i+, two machine-learning datasets for industrial wireless communication. The datasets cover sidelink and cellular communication involving autonomous robots together with localization and sensing data, which can be used to...
Integrated heterodyne laser Doppler vibrometer based on stress-optic frequency shift in silicon nitride
We demonstrate a compact heterodyne Laser Doppler Vibrometer (LDV) based on the realization of optical frequency shift in the silicon nitride photonic integration ! platform (TriPleX). The system comprises a dual-polarization coherent detector...
Hybrid integration of Polymer PICs and InP optoelectronics for WDM and SDM terabit intra-DC optical interconnects
This paper presents a hybrid photonic integration concept based on the use of a polymer motherboard, InP EML arrays and InP PD arrays to realize WDM and SDM Terabit optical engines operating at 100-Gb/s or even at 20! 0-Gb/s per lane. The optical...