3 citations · 3 across the 8 of their papers we have counts for
9 papers
HistReNeRF: Historic Image Relocalisation within Contemporary Neural Radiance Field Reconstructions
Benjamin T. Hughes, Stuart James
Relocalising archival photographs within a contemporary scene model is challenging because historic and modern views can differ in photographic appearance, visible objects, and spa…
ReassembleNet: Learnable Keypoints and Diffusion for 2D Fresco Reconstruction
Adeela Islam, Stefano Fiorini, Stuart James +2
The task of reassembly is a significant challenge across multiple domains, including archaeology, genomics, and molecular docking, requiring the precise placement and orientation o…
Maps from Motion (MfM): Generating 2D Semantic Maps from Sparse Multi-view Images
Matteo Toso, Stefano Fiorini, Stuart James +1
World-wide detailed 2D maps require enormous collective efforts. OpenStreetMap is the result of 11 million registered users manually annotating the GPS location of over 1.75 billio…
Re-assembling the past: The RePAIR dataset and benchmark for real world 2D and 3D puzzle solving
Theodore Tsesmelis, Luca Palmieri, Marina Khoroshiltseva +20
This paper proposes the RePAIR dataset that represents a challenging benchmark to test modern computational and data driven methods for puzzle-solving and reassembly tasks. Our dat…
6DGS: 6D Pose Estimation from a Single Image and a 3D Gaussian Splatting Model
Matteo Bortolon, Theodore Tsesmelis, Stuart James +2
We propose 6DGS to estimate the camera pose of a target RGB image given a 3D Gaussian Splatting (3DGS) model representing the scene. 6DGS avoids the iterative process typical of an…
IFFNeRF: Initialisation Free and Fast 6DoF pose estimation from a single image and a NeRF model
Matteo Bortolon, Theodore Tsesmelis, Stuart James +2
We introduce IFFNeRF to estimate the six degrees-of-freedom (6DoF) camera pose of a given image, building on the Neural Radiance Fields (NeRF) formulation. IFFNeRF is specifically…
PRAGO: Differentiable Multi-View Pose Optimization From Objectness Detections
Matteo Taiana, Matteo Toso, Stuart James +1
Robustly estimating camera poses from a set of images is a fundamental task which remains challenging for differentiable methods, especially in the case of small and sparse camera…
Towards the Reusability and Compositionality of Causal Representations
Davide Talon, Phillip Lippe, Stuart James +2
Causal Representation Learning (CRL) aims at identifying high-level causal factors and their relationships from high-dimensional observations, e.g., images. While most CRL works fo…
3DoF Localization from a Single Image and an Object Map: the Flatlandia Problem and Dataset
Matteo Toso, Matteo Taiana, Stuart James +1
Efficient visual localization is crucial to many applications, such as large-scale deployment of autonomous agents and augmented reality. Traditional visual localization, while ach…