activity
20152024
most citedAutomatic Joint Parameter Estimation from Magnetic Motion Capture Data

183 citations · 310 across the 24 of their papers we have counts for

collaborators

33 papers

cs.CV2024

INQUIRE: A Natural World Text-to-Image Retrieval Benchmark

Edward Vendrow, Omiros Pantazis, Alexander Shepard +5

We introduce INQUIRE, a text-to-image retrieval benchmark designed to challenge multimodal vision-language models on expert-level queries. INQUIRE includes iNaturalist 2024 (iNat24…

cs.CV2024★ 8 cited

Deep learning-based ecological analysis of camera trap images is impacted by training data quality and quantity

Peggy A. Bevan, Omiros Pantazis, Holly Pringle +10

Large image collections generated from camera traps offer valuable insights into species richness, occupancy, and activity patterns, significantly aiding biodiversity monitoring. H…

cs.CV2023★ 1 cited

Two-View Geometry Scoring Without Correspondences

Axel Barroso-Laguna, Eric Brachmann, Victor Adrian Prisacariu +2

Camera pose estimation for two-view geometry traditionally relies on RANSAC. Normally, a multitude of image correspondences leads to a pool of proposed hypotheses, which are then s…

cs.CV2023

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…

cs.GR2023★ 183 cited

Automatic Joint Parameter Estimation from Magnetic Motion Capture Data

James F. O'Brien, Robert E. Bodenheimer, Gabriel J. Brostow +1

This paper describes a technique for using magnetic motion capture data to determine the joint parameters of an articulated hierarchy. This technique makes it possible to determine…

cs.CV2022

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…