2 citations · 2 across the 14 of their papers we have counts for
5 papers · 1 filter
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…