2 citations · 4 across the 7 of their papers we have counts for
7 papers · 1 filter
VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field
Fei Xue, Ignas Budvytis, Daniel Olmeda Reino +1
Visual relocalization is a key technique to autonomous driving, robotics, and virtual/augmented reality. After decades of explorations, absolute pose regression (APR), scene coordi…
A Neural Height-Map Approach for the Binocular Photometric Stereo Problem
Fotios Logothetis, Ignas Budvytis, Roberto Cipolla
In this work we propose a novel, highly practical, binocular photometric stereo (PS) framework, which has same acquisition speed as single view PS, however significantly improves t…
Sparse Multi-Object Render-and-Compare
Florian Langer, Ignas Budvytis, Roberto Cipolla
Reconstructing 3D shape and pose of static objects from a single image is an essential task for various industries, including robotics, augmented reality, and digital content creat…
HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation
Akash Sengupta, Ignas Budvytis, Roberto Cipolla
Monocular 3D human pose and shape estimation is an ill-posed problem since multiple 3D solutions can explain a 2D image of a subject. Recent approaches predict a probability distri…
SFD2: Semantic-guided Feature Detection and Description
Fei Xue, Ignas Budvytis, Roberto Cipolla
Visual localization is a fundamental task for various applications including autonomous driving and robotics. Prior methods focus on extracting large amounts of often redundant loc…
IMP: Iterative Matching and Pose Estimation with Adaptive Pooling
Fei Xue, Ignas Budvytis, Roberto Cipolla
Previous methods solve feature matching and pose estimation using a two-stage process by first finding matches and then estimating the pose. As they ignore the geometric relationsh…