6 citations · 9 across the 6 of their papers we have counts for
8 papers
Virtual Occlusions Through Implicit Depth
Jamie Watson, Mohamed Sayed, Zawar Qureshi +4
For augmented reality (AR), it is important that virtual assets appear to `sit among' real world objects. The virtual element should variously occlude and be occluded by real matte…
Removing Objects From Neural Radiance Fields
Silvan Weder, Guillermo Garcia-Hernando, Aron Monszpart +4
Neural Radiance Fields (NeRFs) are emerging as a ubiquitous scene representation that allows for novel view synthesis. Increasingly, NeRFs will be shareable with other people. Befo…
Map-free Visual Relocalization: Metric Pose Relative to a Single Image
Eduardo Arnold, Jamie Wynn, Sara Vicente +5
Can we relocalize in a scene represented by a single reference image? Standard visual relocalization requires hundreds of images and scale calibration to build a scene-specific 3D…
Learning Structured Gaussians to Approximate Deep Ensembles
Ivor J. A. Simpson, Sara Vicente, Neill D. F. Campbell
This paper proposes using a sparse-structured multivariate Gaussian to provide a closed-form approximator for the output of probabilistic ensemble models used for dense image predi…
The GAN that Warped: Semantic Attribute Editing with Unpaired Data
Gara Dorta, Sara Vicente, Neill D. F. Campbell +1
Deep neural networks have recently been used to edit images with great success, in particular for faces. However, they are often limited to only being able to work at a restricted…
Training VAEs Under Structured Residuals
Gara Dorta, Sara Vicente, Lourdes Agapito +2
Variational auto-encoders (VAEs) are a popular and powerful deep generative model. Previous works on VAEs have assumed a factorized likelihood model, whereby the output uncertainty…
Structured Uncertainty Prediction Networks
Gara Dorta, Sara Vicente, Lourdes Agapito +2
This paper is the first work to propose a network to predict a structured uncertainty distribution for a synthesized image. Previous approaches have been mostly limited to predicti…
Lifting Object Detection Datasets into 3D
Joao Carreira, Sara Vicente, Lourdes Agapito +1
While data has certainly taken the center stage in computer vision in recent years, it can still be difficult to obtain in certain scenarios. In particular, acquiring ground truth…