activity
20182022
most citedBuilding Proactive Voice Assistants: When and How (not) to Interact

5 citations · 8 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV20222 cited

LaMAR: Benchmarking Localization and Mapping for Augmented Reality

Paul-Edouard Sarlin, Mihai Dusmanu, Johannes L. Schönberger +5

Localization and mapping is the foundational technology for augmented reality (AR) that enables sharing and persistence of digital content in the real world. While significant prog…

cs.RO2022

Learning to Simulate Realistic LiDARs

Benoit Guillard, Sai Vemprala, Jayesh K. Gupta +4

Simulating realistic sensors is a challenging part in data generation for autonomous systems, often involving carefully handcrafted sensor design, scene properties, and physics mod…

cs.CV2020

Cross-Descriptor Visual Localization and Mapping

Mihai Dusmanu, Ondrej Miksik, Johannes L. Schönberger +1

Visual localization and mapping is the key technology underlying the majority of mixed reality and robotics systems. Most state-of-the-art approaches rely on local features to esta…

cs.HC20205 cited

Building Proactive Voice Assistants: When and How (not) to Interact

O. Miksik, I. Munasinghe, J. Asensio-Cubero +17

Voice assistants have recently achieved remarkable commercial success. However, the current generation of these devices is typically capable of only reactive interactions. In other…

cs.CV20191 cited

Live Reconstruction of Large-Scale Dynamic Outdoor Worlds

Ondrej Miksik, Vibhav Vineet

Standard 3D reconstruction pipelines assume stationary world, therefore suffer from `ghost artifacts' whenever dynamic objects are present in the scene. Recent approaches has start…

cs.SD2019

Static Visual Spatial Priors for DoA Estimation

Pawel Swietojanski, Ondrej Miksik

As we interact with the world, for example when we communicate with our colleagues in a large open space or meeting room, we continuously analyse the surrounding environment and, i…