2 citations · 2 across the 14 of their papers we have counts for
15 papers
SceneHI: High-Resolution 3D-Consistent Scene Texturing with Controllable Illumination
Athanasios Tragakis, Marco Aversa, Daniela Ivanova +4
SceneHI is a framework that lifts high-resolution, illumination-aware priors from 2D diffusion models to perform 3D texture synthesis. It is the first to demonstrate that high-reso…
Complete virtual unwrapping and reading of a rolled Herculaneum papyrus
Giorgio Angelotti, Stephen Parsons, Federica Nicolardi +24
The carbonized papyri from Herculaneum preserve the only large-scale library to survive from classical antiquity, but many unopened rolls remain unread because physical opening ris…
Neural 3D Reconstruction of Planetary Surfaces from Descent-Phase Wide-Angle Imagery
Melonie de Almeida, George Brydon, Divya M. Persaud +2
Digital elevation modeling of planetary surfaces is essential for studying past and ongoing geological processes. Wide-angle imagery acquired during spacecraft descent promises to…
Ink Detection from Surface Topography of the Herculaneum Papyri
Giorgio Angelotti, Federica Nicolardi, Paul Henderson +1
Reading the Herculaneum papyri is challenging because both the scrolls and the ink, which is carbon-based, are carbonized. In X-ray radiography and tomography, ink detection typica…
Splat-Portrait: Generalizing Talking Heads with Gaussian Splatting
Tong Shi, Melonie de Almeida, Daniela Ivanova +2
Talking Head Generation aims at synthesizing natural-looking talking videos from speech and a single portrait image. Previous 3D talking head generation methods have relied on doma…
Pixel-to-4D: Camera-Controlled Image-to-Video Generation with Dynamic 3D Gaussians
Melonie de Almeida, Daniela Ivanova, Tong Shi +2
Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an essential component for intelligent…
Virtually Unrolling the Herculaneum Papyri by Diffeomorphic Spiral Fitting
Paul Henderson
The Herculaneum Papyri are a collection of rolled papyrus documents that were charred and buried by the famous eruption of Mount Vesuvius. They promise to contain a wealth of previ…
Environment-Aware Channel Inference via Cross-Modal Flow: From Multimodal Sensing to Wireless Channels
Guangming Liang, Mingjie Yang, Dongzhu Liu +2
Accurate channel state information (CSI) underpins reliable and efficient wireless communication. However, acquiring CSI via pilot estimation incurs substantial overhead, especiall…
Divide and Conquer Self-Supervised Learning for High-Content Imaging
Lucas Farndale, Paul Henderson, Edward W Roberts +1
Self-supervised representation learning methods often fail to learn subtle or complex features, which can be dominated by simpler patterns which are much easier to learn. This limi…
Actively Inferring Optimal Measurement Sequences
Catherine F. Higham, Paul Henderson, Roderick Murray-Smith
Measurement of a physical quantity such as light intensity is an integral part of many reconstruction and decision scenarios but can be costly in terms of acquisition time, invasio…
ARTeFACT: Benchmarking Segmentation Models on Diverse Analogue Media Damage
Daniela Ivanova, Marco Aversa, Paul Henderson +1
Accurately detecting and classifying damage in analogue media such as paintings, photographs, textiles, mosaics, and frescoes is essential for cultural heritage preservation. While…
Unsupervised Segmentation by Diffusing, Walking and Cutting
Daniela Ivanova, Marco Aversa, Paul Henderson +1
We propose an unsupervised image segmentation method using features from pre-trained text-to-image diffusion models. Inspired by classic spectral clustering approaches, we construc…
State-of-the-Art Fails in the Art of Damage Detection
Daniela Ivanova, Marco Aversa, Paul Henderson +1
Accurately detecting and classifying damage in analogue media such as paintings, photographs, textiles, mosaics, and frescoes is essential for cultural heritage preservation. While…
Sampling 3D Gaussian Scenes in Seconds with Latent Diffusion Models
Paul Henderson, Melonie de Almeida, Daniela Ivanova +1
We present a latent diffusion model over 3D scenes, that can be trained using only 2D image data. To achieve this, we first design an autoencoder that maps multi-view images to 3D…
Denoising Diffusion via Image-Based Rendering
Titas Anciukevičius, Fabian Manhardt, Federico Tombari +1
Generating 3D scenes is a challenging open problem, which requires synthesizing plausible content that is fully consistent in 3D space. While recent methods such as neural radiance…